Theodoros G Kostis Phd Thesis

Inverse Synthetic Aperture Radar Simulators as Software-defined Countermeasure Systems Department of Information & Communication Systems Engineering, University of the Aegean

Theodoros G Kostis

Phd Thesis

Reviewer List S Katsikas S Gritzalis K Lambrinoudakis N Nikitakos T Simos P Frangos S Likothanassis

2009

Â

I would like to dedicate this thesis to my loving parents Georgios and Maria Kostis.

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Acknowledgements The positive environment that was provided to me by my parents Georgios and Maria Kostis, of my sister Lilla and our dog Phaedra has been an integral factor in the completion of this endeavour and envision into science. Special thanks go to my lifelong friends Pete Delimaras, George Koutsoulis, Kostas Pliakos and Kostas Kefalas.

I would like to thank my supervisor Prof. Sokratis Katsikas of the University of Piraeus for the constant help and encouragement without which this project would not have been possible.

Sincere acknowledgments to Prof. Chris Baker of the Australian National University and Prof. Hugh Griffiths of University College London for subject matter expert help in the beginning of this research effort.

Sincere thanks to Maria Diakaki for helping with the multiple target input data descriptions and to Konstantinos Galanis and Athanasios Goudosis for their constant help, without which this project would not have been possible.

I would also like to thank all reviewers either eponymous or anonymous of this work for their valuable and constructive comments.

This research project has been carried out at the Department of Information & Communications Systems Engineering, University of the Aegean, Karlovassi, Samos 83200, Greece.

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Abstract Modern air defence at sea doctrines call for new shipborne surveillance and tracking systems that are based on software implementations, like software-defined radar systems. This thesis contributes to investigations in the context of the ever-demanding need to forge the other side of the same coin which is countermeasures implementation for electronic protection from high range resolution sensors based again on softwaredefined radar concepts and principles.

The first part of this thesis looks at the problem of devising countermeasures for the protection of naval targets. The analysis of the introductory background information introduces the need for this project. And the literature review lays the foundations for the scientific problem-based research demands.

The second part of the thesis is then focused on the amalgamation of software and radar engineering in order to increase the verisimility issues of false targets. This topic has not received extensive coverage in the literature since its application is primarily in the defence sector. Simulation results are based on a controlled experiment environment that is easy to verify and validate using formal methods. The outcome of the experiment lays the foundations of the Software-defined Countermeasure System.

The remainder of the thesis is then focused on further investigations in the field of computer networks warfare. The conceptual model from the electronic warfare case is extended in order to determine the domain reusability depth factor.

The thesis concludes with the statement that the acquired Software-defined Countermeasure Systems concepts and techniques can be used in an effective and adaptable manner in order to provide deception countermeasures for both electronic warfare and computer networks warfare fields, which both are elements of the domain of information warfare.

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Περίληψη Τίτλος:

Οι εξομοιωτές ραντάρ αντίστροφης συνθετικής κεραίας

ως λογισμικοριζόμενα συστήματα ηλεκτρονικών αντίμετρων.

Το σύγχρονο δόγμα ναυτικής άμυνας απο αεροπορικές απειλές επιζητά τα πλεονεκτήματα που απορρέουν από συστημάτα ραντάρ υψηλής ευκρίνειας βασισμένα σε λογισμικοριζόμενη φιλοσοφία και αρχιτεκτονική. Αυτή η διατριβή ασχολείται με την άλλη πλευρά του ίδιου νομίσματος που είναι η υλοποίηση συστημάτων αντίμετρων για συστήματα ραντάρ υψηλής ευκρίνειας όπως αυτά απαιτούνται για την εναέρια προστασία ενός ναυτικού στόχου.

Το πρώτο μέρος εξετάζει το πρόβλημα της προστασίας των ναυτικών στόχων. Η ανάλυση των εισαγωγικών βασικών πληροφοριών εισάγει την ανάγκη για την διεξαγωγή αυτού του ερευνητικού προγράμματος.

Η βιβλιογραφική ανασκόπηση που

ακολουθεί θέτει τα θεμέλια για την επιστημονική αντιμετώπιση του προαναφερθέντος προβλήματος. Η λύση που προτείνεται είναι η χρησιμοποίηση ενός εξομοιωτή για την δημιουργία πολλαπλών μη αληθινών στόχων με απώτερο σκοπό τον αποπροσανατολισμό και την σύγχυση της αεροπορικής απειλής.

Το δεύτερο μέρος χρησιμοποιεί διακλαδικά τα πεδία της μηχανικής λογισμικού και μηχανικής συστημάτων ραντάρ προκειμένου να αυξήσει το ποσοστό της αληθοφάνειας των προαναφερθέντων μη αληθινών στόχων. Το θέμα της αληθοφάνειας δεν έχει λάβει εκτενή κάλυψη στην ακαδημαική λογοτεχνία επειδή μόλις τώρα μπορεί να γίνει ο εποικοδομητικός συνδυασμός μεταξύ λογισμικού και υλικού ραντάρ για αυτό τον σκοπό.

Τα αποτελέσματα προσομοίωσης του μη αληθινού ναυτικού στόχου

είναι βασισμένα σε ένα πείραμα ελεγχόμενου περιβάλλοντος που είναι εύκολο να ελεγχθεί και να επικυρωθεί με τη χρησιμοποίηση επίσημων μεθόδων ταυτοποίησης και επαλήθευσης της ορθότητας του. Η έκβαση αυτού του ελεγχόμενου πειράματος θέτει τα θεμέλια του λογισμικοριζόμενου συστήματος αντίμετρων αφού προσφέρει αποδεκτή απόδειξη εφικτότητας της σχετιζόμενης καινοτόμου ιδέας.

Το τρίτο μέρος στρέφεται έπειτα σε περαιτέρω έρευνες στον τομέα του Ηλεκτρον-

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ικού Πολέμου για Δίκτυα Ηλεκτρονικών Υπολογιστών. Το εννοιολογικό πρότυπο από την περίπτωση του ηλεκτρονικού πόλεμου για την ναυτική προστασία επιτρέπει την επαναχρησιμοποίηση της μεθοδολογίας και σε αυτή την περίπτωση.

Το συμπέρασμα της διατριβής είναι ότι μια λογισμικοριζόμενη αρχιτεκτονική βασισμένη σε εξομοιωτή επιτρέπει την δημιουργία συστημάτων αντίμετρων που μπορούν να χρησιμοποιηθούν κατά τρόπο αποτελεσματικό και ευέλικτο για την παροχή ηλεκτρονικών αντίμετρων για όλο το φάσμα του Πληροφοριακού Πολέμου.

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Declaration

This work contains no material which has been accepted for the award of any other degree or diploma in any university or other tertiary institution and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text.

I give consent to this copy of my thesis, when deposited in the University of the Aegean Library, being made available in all forms of media, now and hereafter known.

Athens, 15th October, 2009 Theodoros G. Kostis

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Approval THIS DISSERTATION ENTITLED

"INVERSE SYNTHETIC APERTURE RADAR SIMULATORS AS SOFTWARE-DEFINED COUNTERMEASURE SYSTEMS" by Theodoros G. Kostis has been approved by the Department of Information & Communication Systems Engineering, University of the Aegean, Karlovassi, Samos, Hellas.

Examiner: Prof. Stephanos Gritzalis

Examiner: Prof. Sokratis Katsikas

Examiner: Prof. Nikitas Nikitakos

Examiner: Prof. Konstantinos Lambrinoudakis

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Publications Conferences ∙ Kostis T. G., Baker C. J., Griffiths H. D., 2005, Interferometric Inverse Synthetic Aperture Radar, LCS, University College London, London, England. ∙ Kostis T. G., Baker C. J., Griffiths H. D. 2006, An Interferometric ISAR System Model for Automatic Target Identification, EUSAR 2006, Dresden, Germany. ∙ Kostis T. G., Katsikas S.K., 2007, Three-Dimensional Multiple Layer Extended Target Modeling for ISAR Studies in Target Identification, Panhellenic Conference on Informatics, Patras, Greece. ∙ Kostis T. G., 2008, Simulator Implementation of an Inverse Synthetic Aperture Radar System for an Extended Naval Target in a Three Dimensional Synthetic Environment, pp.366-371, Tenth International Conference on Computer Modeling and Simulation (UKSIM 2008), 2008, Cambridge, England. ∙ Kostis T. G., 2008, Glint Effects Simulation for an Extended Naval Target using an Interferometric-ISAR System Model, In European Synthetic Aperture Radar Conference (EUSAR 2008), Friedrichschafen, Germany. ∙ Kostis T. G., Galanis K. G., Katsikas S. K., 2008, Simulator Implementation of an IF-ISAR System for Studies in Target Glint, In Panhellenic Conference on Informatics, pp.140-144, Samos, Greece. ∙ Kostis T. G., 2008, Proof of Concept for the Extensibility Attribute of an ISAR Simulator for Studies in Target Glint, IST 2008 Workshop, Chania, Greece. ∙ Kostis T. G., 2009, Inverse Synthetic Aperture Radar Simulators as Softwaredefined Countermeasure Systems: Security by Obfuscation and Deception for Electronic & Computer Networks Warfare, Book Chapter in Modelling, Simulation and Optimization, IN-TECH Publishing. ∙ Kostis T. G., Galanis K. G., Nikitakos N. V., 2009, Interferometric Inverse Synthetic Aperture Radar Software: Analysis for Air Defence at Sea, NATO SET-136 Software Radar Specialist’s Meeting, June 23-25, Lisbon, Portugal, NATO UNCLASSIFIED.

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∙ Kostis T. G., 2009, Applying Simulator-defined Radar Countermeasure Systems Techniques to Computer Network Security Issues, 3rd European Modelling Symposium, Athens, Greece.

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Journals ∙ Kostis T. G., Katsikas S. K., 2009, Inverse Synthetic Aperture Radar Simulator Implementation for an Extended Naval Target for Electronic Warfare Applications, International Journal of Simulation: Systems, Science and Technology. ∙ Kostis T. G., Galanis K. G., Katsikas S. K., 2009, Angular Glint Effects Generation for False Naval Target Verisimility Requirements, Institute of Physics Measurement Science and Technology Electronic Journal.

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Contents

Dedication

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Acknowledgements

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Abstract

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List of Figures

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List of Tables

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Preliminary Investigation 1

Problem-based Research 1.1 Introduction . . . . . . . .

1.2 Statement of the Problem .

1.3 Problem Statement . . . .

1.4 Motivation . . . . . . . . .

1.5 Contribution of the Thesis 1.6 Challenges . . . . . . . . .

1.7 Thesis Outline . . . . . . .

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Part I

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Deception in Naval Defence 2.1 World War I & World War II Eras . .

2.2 Modern Naval Defence (1960 - 2010) 2.3 Future Naval Defence Requirements .

2.4 Chapter Conclusions . . . . . . . . .

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Literature Review 3.1 The demand for a solution to the reinvented problem 3.1.1 ISAR Simulators . . . . . . . . . . . . . . .

3.1.2 Coherent Deception Techniques . . . . . . .

3.2 Chapter Conclusions . . . . . . . . . . . . . . . . .

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Part II

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ISAR Simulator Implementation for Electronic Warfare 4.1 ISAR Countermeasures Requirements Engineering . . . . . . . . .

4.1.1 End-User Requirements . . . . . . . . . . . . . . . . . . .

4.1.2 Verisimility Requirements . . . . . . . . . . . . . . . . . .

4.1.3 Domain Requirements . . . . . . . . . . . . . . . . . . . .

4.1.4 Functional Requirements . . . . . . . . . . . . . . . . . . .

4.2 Conceptual Modelling I: False Naval Target Generator . . . . . . .

4.2.1 Application Domain Definition . . . . . . . . . . . . . . .

4.2.2 Problem Space Decomposition . . . . . . . . . . . . . . . .

4.2.3 Entity Abstraction Degree . . . . . . . . . . . . . . . . . .

4.2.4 Entity Relationship Identification . . . . . . . . . . . . . .

4.3 Conceptual Modelling II: Angular Glint Enhancement . . . . . . . .

4.3.1 Application Domain Definition . . . . . . . . . . . . . . .

4.3.2 Problem Space Decomposition . . . . . . . . . . . . . . . .

4.3.3 Entity Abstraction Degree . . . . . . . . . . . . . . . . . .

4.3.4 Entity Relationship Identification . . . . . . . . . . . . . .

4.4 Implementation Procedures . . . . . . . . . . . . . . . . . . . . . .

4.4.1 Synthetic Environment Abstraction . . . . . . . . . . . . .

4.4.2 Entity-Relationship Modelling for ISAR Processing . . . .

4.4.3 Three-Dimensional Single Layer Extended Target Modelling 4.4.4 Naval Target Platform Increased Complexity Approach . . .

4.4.4.1 Parallelogram Model . . . . . . . . . . . . . . .

4.4.4.2 More Model . . . . . . . . . . . . . . . . . . . .

4.4.4.3 More Detailed Model . . . . . . . . . . . . . . .

4.4.4.4 Multiple Deck Model . . . . . . . . . . . . . . .

4.4.4.5 High Reflectivity on Lower Superstructure . . . .

4.4.5 Glint Effects Addition . . . . . . . . . . . . . . . . . . . .

4.4.6 Module Interconnection Language . . . . . . . . . . . . . .

4.4.7 Pace Engine . . . . . . . . . . . . . . . . . . . . . . . . . .

4.4.7.1 Roll Motion . . . . . . . . . . . . . . . . . . . .

4.4.8 Inverse Scattering . . . . . . . . . . . . . . . . . . . . . . .

4.4.8.1 Range-Doppler Process . . . . . . . . . . . . . .

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4.5 5

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Chapter Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . .

Software System Quality Factor 5.1 Quality Factor Definition . . . . . . . . . . . . . . .

5.1.1 Checklist of Software Quality Factors . . . .

5.2 Verification . . . . . . . . . . . . . . . . . . . . . .

5.2.1 ISAR Module Verification . . . . . . . . . .

5.2.2 Glint Effects Module Verification . . . . . .

5.2.2.1 Three Dimensional Representation 5.2.2.2 Two Dimensional Representation .

5.2.2.3 Rotation Vector Contribution . . .

5.3 Validation . . . . . . . . . . . . . . . . . . . . . . .

5.3.1 ISAR Module Validation . . . . . . . . . . .

5.3.2 Glint Effects Module Validation . . . . . . .

5.3.2.1 Figure Type I . . . . . . . . . . .

5.3.2.2 Figure Type II . . . . . . . . . . .

5.3.2.3 Figure Type III . . . . . . . . . . .

5.3.2.4 Maximum Glint Criterion . . . . .

5.4 Chapter Conclusions . . . . . . . . . . . . . . . . .

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Simulator-defined Countermeasure System Concept 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.2 SdCS System Design . . . . . . . . . . . . . . . . . . . . . .

6.2.1 Distance Measurements . . . . . . . . . . . . . . . .

6.2.2 Radio Frequency Interferometer . . . . . . . . . . . .

6.2.3 Movement of the False Target . . . . . . . . . . . . .

6.2.4 Glints Effects Injection . . . . . . . . . . . . . . . . .

6.2.5 Digital Signal Processing Use-Case . . . . . . . . . .

6.3 Proof of Concept with a Controlled Experiment . . . . . . . .

6.4 False Target Generation Results . . . . . . . . . . . . . . . .

6.4.1 Approaching Missile Scenario . . . . . . . . . . . . .

6.4.2 Stand-Off Aircraft Surveillance and Tracking Scenario 6.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.6 Chapter Conclusions . . . . . . . . . . . . . . . . . . . . . .

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Part III

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Domain Reusability for Computer Networks Warfare 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7.2 Computer Networks Warfare . . . . . . . . . . . . . . . . . . .

7.3 Elements of Domain Reusability . . . . . . . . . . . . . . . . .

7.4 Domain Reusability Depth Factor . . . . . . . . . . . . . . . .

7.4.1 Conceptual Modelling for False Registration Authorities 7.4.1.1 Application Domain Definition . . . . . . . .

7.4.1.2 Problem Space Decomposition . . . . . . . .

7.4.1.3 Entity Abstraction Degree . . . . . . . . . . .

7.4.1.4 Entity Relationship Identification . . . . . . .

7.4.2 Implementation Techniques for PKI Databases . . . . .

7.4.2.1 Modularity . . . . . . . . . . . . . . . . . . .

7.4.2.2 Increased Complexity . . . . . . . . . . . . .

7.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Project Assessment

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Conclusions 8.1 The SdCS concept: A new approach to coherent countermeasures 8.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8.2.1 Enrichment of the software code . . . . . . . . . . . . . .

8.2.2 Domain reusability . . . . . . . . . . . . . . . . . . . . .

8.2.3 Decoy platform elaboration . . . . . . . . . . . . . . . .

8.2.4 Code execution speed-up . . . . . . . . . . . . . . . . . .

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References

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Index

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Equations Index

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List of Figures

2.1 2.2 2.3 2.4

USS Leviathan Dazzle Camo . . . .

Gloire Horizontal Dazzle Camo . .

Kriegsmarine Dazzle Camo Patterns KMS Bismarck Dazzle Camo . . . .

4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14 4.15 4.16 4.17 4.18 4.19 4.20 4.21

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Domain Conceptual Modelling . . . . . . . . . . . . . . . . . .

Conventional Radar Antenna . . . . . . . . . . . . . . . . . . .

Phased Array Antenna . . . . . . . . . . . . . . . . . . . . . .

ISAR Theory . . . . . . . . . . . . . . . . . . . . . . . . . . .

General Depiction of a High Range Resolution Process . . . . .

ISAR Geometry . . . . . . . . . . . . . . . . . . . . . . . . . .

Entity-Relationship Identification . . . . . . . . . . . . . . . . .

Strategic tasks with expendable ISAR capable decoy systems . .

The position of the false target generator subsystem. . . . . . . .

Target Map . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Glint Geometry . . . . . . . . . . . . . . . . . . . . . . . . . .

Single Layer Model System Design . . . . . . . . . . . . . . .

Multiple Layer Model System Design . . . . . . . . . . . . . .

Higher reflectivity on higher superstructure only . . . . . . . . .

Higher reflectivity on deck levels . . . . . . . . . . . . . . . . .

Higher Superstructure . . . . . . . . . . . . . . . . . . . . . . .

Deck line and middle superstructure . . . . . . . . . . . . . . .

Packet breakdown analysis (sample) . . . . . . . . . . . . . . .

Module Interconnection Language (MIL) . . . . . . . . . . . .

Digital World Implementation . . . . . . . . . . . . . . . . . .

Theoretical Implementation of Inverse Scattering (Polar Format proximation) . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.22 Range-Doppler Process . . . . . . . . . . . . . . . . . . . . . .

5.1 5.2

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Uniform amplitude/phase model, Model 1 (a) Slant Range Profile (b) ISAR image, Model 2 (c) Slant Range Profile (d) ISAR image . . . .

Diverse amplitude/phase single layer model with added phase delay effects, Single Layer (a) Slant Range Profile (b) ISAR image . . . . .

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5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 5.13 5.14 5.15 5.16

Validation procedure . . . . . . . . . . . . . . . . . . . . . . . . . .

Simulation complexity history . . . . . . . . . . . . . . . . . . . . .

Glint Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Verification Task I - Glint module disengaged produces no distortion to the false target . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Verification Task II - Glint module engaged at one point produces a single distortion to the false target . . . . . . . . . . . . . . . . . . .

Long Distance High Altitude Angular Glint Effects Mask Injection . .

Zero Distance Low Altitude Angular Glint Effects Mask Injection . .

Long Distance High Altitude Wavefront Distortion Effects at the Threat Zero Distance Low Altitude Wavefront Distortion Effects at the Threat Long Distance High Altitude 3D Motion Degree Measurement . . . .

Zero Distance Low Altitude 3D Motion Degree Measurement . . . .

Long Distance High Altitude Extreme Angular Glint Effects Mask Injection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Long Distance High Altitude Extreme Wavefront Distortion Effects at the Threat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Long Distance High Altitude 3D Motion Degree Measurement shows strange target properties . . . . . . . . . . . . . . . . . . . . . . . . .

6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11

Requirements Draft for the SdCS Project . . . . . . . . . . . . . . . .

Software Modules Interconnection . . . . . . . . . . . . . . . . . . .

SdCS Description . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Software Modules Inteconnection . . . . . . . . . . . . . . . . . . .

Distance proposed calculation . . . . . . . . . . . . . . . . . . . . .

Interferometer proposed configuration . . . . . . . . . . . . . . . . .

Movement of the false target . . . . . . . . . . . . . . . . . . . . . .

Prominent and interfering point scatterers . . . . . . . . . . . . . . .

Use Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Threat Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

A1 - Glint at the target - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

6.12 A2 - Glint at the radar - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . .

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6.13 A3 - Slant Range Profile - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

6.14 A4 - ISAR Image - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.15 B1 - Glint at the target - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.16 B2 - Glint at the radar - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.17 B3 - Slant Range Profile - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

6.18 B4 - ISAR Image - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.19 C1 - Glint at the target - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.20 C2 - Glint at the radar - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.21 C3 - Slant Range Profile - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.22 C4 - ISAR Image - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.23 D1 - Glint at the target - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.24 D2 - Glint at the radar - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.25 D3 - Slant Range Profile - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.26 D4 - ISAR Image - Missile 1853m, 20m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.27 E1 - Glint at the target - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

6.28 E2 - Glint at the radar - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

6.29 E3 - Slant Range Profile - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . .

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6.30 E4 - ISAR Image - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 6.31 F1 - Glint at the target - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 136 6.32 F2 - Glint at the radar - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 137 6.33 F3 - Slant Range Profile - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 138 6.34 F4 - ISAR Image - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 6.35 G1 - Glint at the target - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 140 6.36 G2 - Glint at the radar - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 141 6.37 G3 - Slant Range Profile - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 142 6.38 G4 - ISAR Image - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 6.39 H1 - Glint at the target - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 144 6.40 H2 - Glint at the radar - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 145 6.41 H3 - Slant Range Profile - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . 146 6.42 H4 - ISAR Image - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 7.1

An 80s personal computer behaved like a point scatterer in terms of connectivity like the inverse scattering depiction on a plan position indicator (PPI) radar screen. . . . . . . . . . . . . . . . . . . . . . . 154

7.2

A modern personal computer is an extended target like its naval equivalent. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

7.3

Domain reusability depth factor estimation. . . . . . . . . . . . . . . 156

7.4

Computer Networks Warfare domain reusability . . . . . . . . . . . . 158

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7.5 7.6 7.7 7.8

Domain analysis between EW and CNW cases. . . . . . . . . . . . . 159 E-R Identification is the same for the electronic warfare and the computer network warfare cases. . . . . . . . . . . . . . . . . . . . . . . 163 Modularity in PKI Databases. . . . . . . . . . . . . . . . . . . . . . . 164 Increased complexity in maintaining a Public Key Infrastructure Database system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

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List of Tables

2.1

Review of Naval Warfare . . . . . . . . . . . . . . . . . . . . . . . .

23

4.1 4.2 4.3

Electronic Warfare Entities . . . . . . . . . . . . . . . . . . . . . . .

Electronic Warfare Processes . . . . . . . . . . . . . . . . . . . . . .

Reflectivity Solution Values per Resolution Cell. . . . . . . . . . . .

48 49 55

5.1 5.2 5.3

Glint Generation Algorithm - Input Stage . . . . . . . . . . . . . . .

Glint Generation Algorithm - Transfer Function Stage . . . . . . . . .

Glint Generation Algorithm - Output Stage . . . . . . . . . . . . . .

84 85 86

6.1

Threat Assessment Scenario . . . . . . . . . . . . . . . . . . . . . . 114

7.1 7.2

Computer Networks Warfare Entities . . . . . . . . . . . . . . . . . . 160 Computer Networks Warfare Processes . . . . . . . . . . . . . . . . 161

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Preliminaries Needed: A good problem!

Demanded: A solvable problem!

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All warfare is based on deception. The means by which enlightened rulers and sagacious generals moved and conquered others was advance knowledge. Of the five spies to be employed note the expendable spy: spreads disinformation, false information that is, outside the state.

- Sun Tzu and Sun Pin, The Art of War, c. 6th Century BC

1

Problem-based Research

This research is conducted around the electronic warfare problem of finding the next generation of coherent countermeasures against radar systems that can image extended naval targets. The research structure incorporates elements from software engineering as they may be applied to radar systems engineering. Finally the overall research effort considers how the assessment of knowledge from the acquired electronic warfare results will impact the field of security by obscurity countermeasures for information warfare in the future.

1.1

Introduction

In the eighth episode of season five of the 1962 series of "Mission: Impossible" head operative Peter Graves inflates a life-sized plastic decoy detailing himself so to confuse in order to escape his opposing counterparts. It comes as no surprise that this episode is distinctively titled "Decoy". A decoy is a person, device or event of at least lesser and of preferable minimal value that serves purposes of security by distraction and obfuscation. This function is performed by introducing one or many replicas of a person, device or event in order to conceal the valuable original asset from the adversary interest groups that are actively seeking the friendly beneficiary with malevolent intent. In this case the valuable asset is a military naval vessel or fleet that requires protection from airborne threats of enhanced electromagnetic nature or advanced radar

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Chapter 1

surveillance and tracking sensor technologies.

This work promotes the thesis that the current state of affairs in the field of modern air defence at sea demands distraction and obfuscation solutions based on software defined radar systems. Specifically the generation of the concept of coherent deception that is used to oppose high range resolution radar systems is argued to be more straightforward when performed by software-defined radar systems based on simulator sub-systems than by using dedicated to particular countermeasures hardware platforms of electronic protection for two main reasons. First with a simulator system it is easier to adjust the false target properties to the actual target properties so the adversary will not be able to distinguish the real target thus providing initial targeting hindrances.

Secondly the convenience of adding reality enhancement effects, like the various noise and glint elements found in an actual returned high range resolution radar signal, thus increasing the confidence of the adversary regarding the validity of the contact. Therefore with a simulator system it is easier to adapt to sensor technology limitations and to incorporate the laws of physics in the countermeasure design always keeping in mind that the ultimate goal is to deceive the radar operator and radar system loop with emphasis on the human element.

1.2

Statement of the Problem

The statement of the problem is a brief outline of the problem that this study addresses (37)[Ellis, 2008, p. 27]. This thesis answers the question : What should be done for adaptively and effectively counter threats in the modern theaters of information warfare for naval defence and why?

The short answer is: The threats in the modern theaters of information warfare affect elements from the fields of electronic warfare and computer networks warfare. In this thesis it will be proven that an adaptive and effective solution is the concept of a Simulator-defined Countermeasure System (SdCS). Such a system is based on software-defined concepts

Problem-based Research

5

and techniques that can be used in an efficient and custom manner in order to provide deception countermeasures. Because in this manner false targets can be readily synthesized that can be crafted to be as realistic as possible. The purpose is to deceive the man-machine loop of the adversary identification process. Moreover the main proof is in the form of a controlled experiment that involves the generation of a false naval target in order to provide electronic warfare security by obscurity functions against high resolution imaging systems. This evidence is further corroborated by extensions to the field of computer networks warfare by presenting a conceptual modelling analysis of a false registration authority. The thesis concludes with the result that the utilisation of false targets is a good solution to modern threats because although the creation of threat cannot be stopped the hiding of the friendly assets is a legitimate and productive solution.

1.3

Problem Statement

The problem statement addresses all questions regarding the validity of the argumentation in conceptual and realization terms. Furthermore all valid research must be based on a well-articulated, well-supported and well-argued problem statement (37)[Ellis, 2008, p.27]. A research problem is defined as a general issue, concern or controversy addressed in research. It must integrate concepts and theoretical perspectives of the literature into the problem to be addressed. It must include the following vital elements: ∙ The current state differs from the ideal state. ∙ There is not an acceptable solution available.

The Problem Statement of this work is as follows: Countermeasures for coherent radar systems have proven to be quite difficult to implement due to technological barriers and overall confidentiality in this field of information warfare (123)[Pace, 2002], (118)[Neri, 2007], (11)[Balwindson, 2008], (110)[Matthes, 2009]. Nevertheless their function of security by obscurity with the generation of multiple false targets that hide the friendly asset is the only method to defeat a high

6

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resolution radar. Barrage noise approaches are not efficient because their effect is canceled out by the integration function of the coherent system. With this information in mind there is only one actual implementation documented in the open literature by (123)[Pace, 2002] where by using an FPGA approach and by demanding rapid calculation of maths several types of false targets are produced from a static lookup table.

But according to (11)[Balwindson, 2008] the countermeasure system must always take into account and adapt to the threat signal’s heading and velocity vectors in real time.

Therefore there is a need to adapt the false target to the depression angle and elevation characteristics of the threat in order to increase the verisimility of the stratagem.

Moreover according to (118)[Neri, 2007] angular glint effects must be incorporated in the false target mask which makes the task ever more difficult. The incorporation of angular glint effects is a very recent and important element in the implementation process as shown by the works of (110)[Matthes, 2009] and very confidential as the related FGAN work received a NATO RESTRICTED classification in a recent Sensors & Signals conference. The benefits of successful coherent countermeasures implementations have been documented. The solution by (123)[Pace, 2002] can produce many kinds of naval targets. And the solution by (187)[Yuan, 2008] can produce false incoming missiles that induce anxiety to the adversary man-in-the-loop. Although a number of factors have been suggested as important elements in impacting the success of a countermeasure regime for coherent systems, the impact of verisimility issues as a vehicle to induce social engineering practices on the adversary radar operator appears as the authoritative common and highly important foundation. Unfortunately very little attention has been given in literature to exactly what constitutes the optimal organizational culture for an effective increased verisimility concept and how to foster that reality replicating culture. Therefore what is the optimal verisimility solution for coherent countermeasures?

The above question is an active research subject. A representative set of researchers actively involved in a similar research effort is as follows: ∙ (110) Matthes D., 2009, Software Defined Generation of Synthetic Radar False Targets with Angular Deception, FGAN/FHR-PSK. ∙ (123) Pace P. E., Fouts D. J., Ekestrom S., Karow C., 2002, Digital False Target Image Synthesizer for Countering ISAR, IEE Proc., Vol. 149, No. 5, pp. 248257.

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7

∙ (124) Pace P. E., Fouts D. J., Zulaica D. P., 2006, Digital Image Synthesizer: Are enemy sensors really seeing what’s there?, IEEE Aerospace and electronics Systems Magazine, Vol. 24, No. 2, pp. 3-7. ∙ (11) Baldwinson J., Antipov. I., 2008, A Modelling and Simulation Tool for the Prediction of Electronic Attack Effectiveness, Electronic Warfare & Radar Division, Defence Science and Technology Organisation, Bld. 205L, West Avenue, Edinburgh, SA, 5111, Australia.

A valuable reference in order to proceed was (36)[Dunleavy, 2003].

1.4

Motivation

The incentive or reason1 for conducting this research is that a naval target is the most difficult entity that can be camouflaged or blended to its surroundings than any other form of man-made entity.2 Because at daytime a ship clearly stands out against the horizon. And at nighttime even the faintest luminance either natural (moonlight) or mad-made (port lights) will strongly indicate the darker presence of the naval superstructure.

Therefore there is a need to minimize the entropy of the solution space of ship camouflage by finding an appropriate concealment methodology. The challenge would be to maximize the effectiveness of this concealment methodology for actual usage in the real world. In this work this solution is demanded or ordered by the academic community and thus by definition it must be economic, original, rigorous, accurate, correct, drawn upon previous relevant knowledge and eventually clear to the appropriately relevant academic and commercial communities.

1.5

Contribution of the Thesis

The question is that can software engineering help in designing better countermeasure systems for imaging radars and can this methodology and techniques developed are an 1 (16)[Biehler,

1997], (33)[Deci, 1972]

2 http://www.nerdmodo.com/2009/07/naval-artdazzle-camouflage/

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integral part of information warfare domain. This is a new field that research literature is scarce. Therefore the main elements of this thesis are the following in order of appearance:

∙ Historical background information on deception techniques for naval warfare purposes. ∙ A thorough literature review on ISAR simulators and relevant countermeasures pinpointing the need to conduct this research. ∙ Methodology in order to provide a controlled experiment. ∙ Quality factor estimation by verification and validation examples. ∙ Proof of concept resulting in laying the foundations of the Simulator-defined Countermeasure System (SdCS) for air defence at sea purposes ∙ Domain reusability foundations for Computer Networks Warfare. ∙ Establish future research abilities and possibilities.

And the main contributions of this thesis are:

∙ The derivation of a beneficial SdCS proof of concept. ∙ The construction a computer model that can provide increased verisimility levels of a false naval extended target. ∙ The formulation of an implementation methodology that can be applied to all aspects of information warfare which are the fields of electronic warfare and computer networks warfare.

For this project the definition of real world is the realm of human actual experience, practice and application to the field of security engineering and information warfare.

Problem-based Research

1.6

9

Challenges

Rigorous academic contention currently exists for the delivery of a countermeasure product for high resolution radar systems with enhanced verisimility features. This thesis engages in this run to provide the domain requirements, implementation methodology, proof of concept, results commendations and future recommendations that would increase the amount of knowledge in this direction.

The secret to the production of solid practical advice and beneficial experiences for a research investigation is all about making the right moves (23)[Burroughs, 2006].

The time budget is limited and the demand for results is never so much pressing as today. The task is so important that well-established and highly reputable cuttingedge technological organizations, like the NATO RTO Organisation1 , have researchers currently working on this subject.

On the technical side coherent countermeasures need to deduce the spectral coherence of the threat radar. When this task is successful then false targets can be injected into the threat signal. The main point is to be able to persuade the radar operator that the false target is indeed a true contact. The task of presenting plausible false targets that have a high probability of being mistaken as true contacts by taking under consideration the predominant laws of physics and the limitations of current technology is an interdisciplinary problem. The interesting part is that even targets that have reduced verisimility levels can be useful. The final effort is to perform social engineering techniques to the adversary radar operator.

1 http://www.rta.nato.int/

10

1.7

Chapter 1

Thesis Outline

This thesis is organized as follows: Chapter 1 - Problem-based Research This chapter introduces the importance of the problem and the pressing need for an engineering solution.

The main contributions of this chapter is the preliminary justification of the need to embark on this project.

Related Publications: (84) Chapter 2 - Deception in Naval Defence This chapter presents background information relevant to the requirements for camouflage and deception in information warfare particularly for naval operations. The contents establish the actual needs for security by obscurity in real life situations of electronic and computer networks warfare.

The main contributions of this chapter is to establish the real world needs for this project.

Related Publications: (77), (83), (88) Chapter 3 - Literature Review This chapter presents the literature review that is connected to the above actual needs.

The contents identify the existing scientific advances that have been made in order to achieve superiority in information warfare. Analytically here the effort is to introduce the reader to the widest scope of existing ISAR simulators and relevant countermeasures. Then the gap in the research is presented that forms the main research proposal of this work.

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11

The main contributions of this chapter are to provide a comprehensive literature review of ISAR jamming in the open literature. Then identify the research gap that is further needed in order to continue the scientific effort. This chapter mainly helps to clarify the project aims.

Related Publications: (87), (88) Chapter 4 - ISAR Simulator Implementation for EW This chapter presents The Inverse Synthetic Aperture Radar simulator for Electronic Warfare implementation procedures are depicted.

The conceptual modelling of our ISAR simulator for countermeasures is shown. conceptual model construction is presented. There is a review of the related work in the field and the corresponding application domain definitions, problem space decompositions, entity abstraction degrees and entity-relationship identifications. proof of concept is shown in . For the verification task there is the description of the involved mathematical approaches for the glint effect and the speed factor. For the validation task data is created for the three threat scenarios.

The main contributions in this chapter is the depiction of the requirements analysis that dictates the implementation steps in order to produce the bespoke softwaredefined countermeasure system.

Related Publications: (77), (78), (79), (80), (81), (84), (87), (88) Chapter 5 - Software System Quality Factor This chapter presents the quality factor definition for the simulator system, like the verification and validation of the component parts and the overall output of the simulator. Also the module interconnection language of the software system is detailed.

The main contributions in this chapter is to produce a quality factor for the simulator construction.

Related Publications: (80), (82), (83)

12

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Chapter 6 - Simulator-defined Countermeasure System This chapter presents new research concepts that have stemmed for the previous chapters. The product of this research is shown in the form of the Software-define radar countermeasure system concept. It is an idea that is currently rendered possible due to the advances of software engineering. the meaning of the results taken from this proof of concept approach are discussed.

The main contributions in this chapter is to establish the concept of the Simulatordefined Countermeasure System as a system that uses a simulator engine to produce multiple time advances of the input data and present them to an adversary at a later time in order to produce security by obscurity functions.

Related Publications: (85) Chapter 7 - Domain Reusability for Computer Networks Warfare The previous research is shown to be able to be reused in the field of computer networks warfare.

The main contributions in this chapter is to reinforce the statement that electronic warfare and computer networks warfare are communicative vessels that belong to the domain of information warfare.

Related Publications: (80), (84), (86) Chapter 8 - Conclusions Concluding remarks are given together with future literature implications.

The main contributions in this chapter is to provide an evaluation of the research effort and to produce relevant future research possibilities.

Related Publications: (84)

Part I Needed: Naval Protection from ISAR Systems Demanded: A good solution!

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Si vis pacem, para bellum. Therefore, he who wishes peace, should prepare war; he who desires victory, should carefully train his soldiers; he who wants favourable results, should fight relying on skill, not on chance.

(Epitoma Rei Militaris) - Publius Flavius Vegetius Renatus, c. 390 AD

2

Deception in Naval Defence

There are two ways to hide a valuable asset; camouflage painting and embedding in a false target population. Both solutions obey the theorem that the most effective security by obscurity is hiding in plain view. Yet it takes a lot of effort to rely on such skillful deceptions on an actual confrontation. In this chapter the evolution of soft-kill methods is reviewed in order to designate the requirements for the future.

2.1

World War I & World War II Eras

Great Britain depended on naval convoys carrying war supplies from North America.

These cargo vessels of medium to great tonnage were initially painted in variations of uniform gray. In order to stop this influx of supplies the Kriegsmarine1 employed the skillful measures of raider ships disguised as merchant navy (Kormoran HSK-82 ), warships disguised as friendly destroyers (KMS Graf Spee3 ) and most importantly the Untersee-Boots (Submarines, the famous U-994 ) naturally hidden by the deep ocean waters or the dark of the night while on surfaced attacks.

The Commonwealth employed the Q-Ships5 to counter the merchant raider ships. And the Royal Navy in order to counter the raider battleships6 . But the most effective menace of the convoys were the U-Boots. This silent service was highly effective despite the fact that accurate aiming of torpedoes required that the U-Boat commander had to determine from a distance and under inhibiting viewing conditions both the

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Cargo ships in convoy formation were primary targets for the Kriegsmarine

Before radar the U-Boat was the most formidable and silent hunter of the convoys

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speed and heading of the targeted vessel. The challenge was that the U-Boat Captain had to plot a solution that preceded the target. In other words the aiming was not at Plotting the torpedo the current position of the ship but where the ship would be intercepted by the torpedo. solution was a All these calculations had to be done through a periscope therefore a long observation human decision time was needed. Yet the task was quite a routine due to the lack of any camouflage from the Commonwealth ships which made them stand out against the natural colours of sea and sky.

It is important to reinvent a problem when no solution is available

It is important to provide a proof of concept to the reinvented problem

On the other side the Commonwealth gathered initial proposals to camouflage their naval vessels by attempting to blend them into the horizon. Those tests were met with disappointment because naval camouflage is very different from other types of camouflage. The horizon gives a nice contrast and the silhouette of a vessel is highly distinguishable. Then Norman Wilkinson7 , a British naval officer and artist, in 1917, suggested a different approach based on security by obscurity. He reinvented the problem by not trying to make a ship invisible but to prevent it from being hit. The problem was shifted to confusing the adversary human element that decided on the firing solution. For this purpose Wilkinson recommended that ship outer surfaces be painted in high contrast colours with erratic patterns, boldly edged, asymmetrical shapes that utilized optical illusions and vanishing artificial horizons. He called this method as Dazzle Camouflage Painting.

The novelty of the time was being to break up the pattern of the ship itself and confuse the submarine firing solution which was mainly based on human decision as to the vessel’s heading and speed. A poignant example is the SS Leviathan, an American troop transport and former German luxury liner which became a rich pattern of saw-toothed edges and curves that resembled a false horizon vanishing point. It is noteworthy to consider that the captain of a destroyer sent to escort Leviathan across the Atlantic was so confused by the coloration that he had to circle the ship three times in order to determine the direction she was headed. The photograph of the USS Leviathan8 in a dazzle camouflage pattern is shown in Figure 2.1.

Another example is the Gloire9 . The novelty of the artistic camouflage was the horizontal zebra lines. This was a very successful attempt because it contained elements of optical illusions that made the ship’s shape to change in spacial perception, as shown in Figure 2.2.

Deception in Naval Defence

Figure 2.1: USS Leviathan Dazzle Camo

Figure 2.2: Gloire Horizontal Dazzle Camo

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Figure 2.3: Kriegsmarine Dazzle Camo Patterns

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19

Larger tonnage shipping and Battleship Class vessels could paint a silhouette of a smaller vessel, such as a destroyer, on the side against a grey background. This effect lead the submarine captains to miscalculate their firing solutions. Characteristic examples of such Kriegsmarine10 dazzle patterns that reduce the actual size of the ship are shown in Figure 2.3. Initialy dazzle painting was very effective and the rate of daytime sinkings decreased. Nevertheless U-boat attacks on the surface at night were very effective and hard to encounter (111)[McKercher, 2001]. Also on moonlit nights the uniformly dark silhouette of the target vessel could be easily distinguished against the gloomy horizon thus rendering the dazzle pattern ineffective.

During World War II the colours that were present in dazzle painting were dropped Dazzle camo was in favor of a mix of black, white, and gray for most naval vessels and cargo transports. still functional For example optical countermeasures of KMS Bismarck11 to long range observation during WWII were a combination of black and white stripes on her side areas that spanned the battleship from top to bottom. Also there was as a false bow wave on her bow and a false wake on her stern. This dazzle pattern was present as she left Norway on 1941. In

Figure 2.4: KMS Bismarck Dazzle Camo

the era of the Battle of the Atlantic12 above camouflage practices were mostly effective against combat identification since long-range all-weather airborne and shipborne surveillance radar systems were not available. For example, to a distance Bismarck would look like a smaller ship or a convoy of many ships, as shown in Figure (2.4).

In 1943 Fleet Air Arm achieved several decisive victories against the Axis subma- ENIGMA rine fleet. The electronic attack success of the ENIGMA13 machine code cracking cryptanalysis was an early computer was revealing future intelligence about the tactics of the wolf packs14 . Nevertheless networks warfare action

20

Technological novelties can become decisive factors

Part I - Chapter 2

a method was also needed in order to scan for German submarines in open seas from an aerial observatory platform. The answer was the operational introduction during that March of the microwave radar at a wavelength of 10cm (109)[Marvin, 2006].The German submarine force could not come up with a direct electronic countermeasure for this situation. Although an indirect countermeasure was put into operation, called snorkel15 , which could allow the submarine vessels to remain submerged at periscope level thus hidden from the 10cm electromagnetic danger and safely charge their batteries for a longer time. Safe from electromagnetic eyes in the sky this inhaler device was painted in a camouflage motive that either blended with the sea surroundings or looked like a shark’s fin from a distance. We find here the application of the concept of security by obscurity by using the glint of the ocean and the form of creatures of nature as a concealing background.

The other threat to a naval target is the aerial attack

At the same time German research came up with the concept of the Fritz-X16 antiship guided bomb launched from an aerial platform, like the Heinkel He-177 Greif17 and the Dornier Do-21718 . Initially the weapon was victorious, for example the major hit of HMS Warspite19 in Salerno. But no efforts were made to conceal the operational frequency and aileron characteristics of the bomb. In consequence during D-Day the Allies had devised direct countermeasures that could successfully deflect these guided bombs from their targets by jamming their ailerons through their native operational frequency. The overall result was Allied victory (158)[Stavropoulos-1, 2008].

Using security by obscurity is vital to Naval Defence

Therefore the derivation of direct countermeasures that hide the friendly naval assets from their opposing aerial, seafaring and underwater counterparts by using obscurity and distraction principles are of paramount importance to military operations.

2.2 Radar technology can see through optical camouflage

Modern Naval Defence (1960 - 2010)

The advancement of radar technology started to render camouflage patterns ineffective.

Although camouflage practices still remained operational in the submarine service. By the end of World War II warships returned to the uniform grey colorings of the First World War. Nowadays warships are still overall painted flat grey because dazzle optical countermeasures can be scarcely deceiving to the opposition. The electromagnetic

Deception in Naval Defence

21

signature of the superstructure has certain unavoidable high reflectivity points that can be exploited for all-weather distant surveillance and tracking by the opposite radar.

Significant technological advances for radar and sonar were made during 1970 to 2000. In these years important elements were the advancement of high range resolution (HRR) radar and sonar systems. HRR systems are based on the principle of coherence and are termed coherent radars, which in simple terms means that the receiver is looking only for signals that highly resemble the transmitted signal. A filter is matched to this analogy resulting in a high reduction of additive noise factors. This type of radar system can integrate the inverse scattering and is able to perform advanced digital signal processing tasks, like velocity measurements, to the collected data.

With high resolution radar prominent features on naval targets can now be seen

Aircraft platforms received this new technological advancement with priority. Because their operational height allowed a better view of the field resulting in enhanced operational awareness. Although expensive even some missile platforms were equipped with miniaturized high resolution microwave (coherent radar) sensors. In this manner a ship target can be resolved in slant, cross and even height dimensions, while always tracking the superstructure’s most prominent points. Also missiles fired from airborne carriers to targets at sea acquired the advantage of longer operational ranges.

The usual practice of delivering a missile payload to its target became the monopulse20 tracking method. In this way the target is viewed as a collective point that is tracked as a function of time.

Modern warfare is conducted from far distances without optical contact between the adversaries; a characteristic example is the Falklands War

There are two major methods employed in order to protect valuable fleet elements.

First the hard kill method where a live munitions platform is used in order to physically destroy the threat. And the soft kill method which employs decoys and jammers which seek to divert, confuse and if all fails seduce the incoming threat away for the friendly platform.

Soft-kill can be continuously practiced usually without adverse diplomatic consequences

The conclusion of the above analysis is that nowadays high range resolution or wide- Intermediate band synthetic aperture radars like SAR and ISAR systems are capable of generating Conclusions images of target objects (103)[Liu, 2000]. These systems employ high range resolution sensors that have the ability of resolving a target into all its physical dimensions, like slant, cross and height ranges. The importance of the topic comes from the fact

22

New soft-kill requirements against HRR systems are urgently needed!

that such systems usually mounted in either shipborne or airborne platforms are used by the military for classification and identification and even targeting purposes. This fact re-invents the problem of ship defence that was currently covered by conventional electronic warfare concepts. Now the sensor can produce a detailed image of the target in a tomographic manner. The previous countermeasure methods were designed to oppose methods that viewed the target as a collective point. Therefore there is an overall need for the drafting of new requirements for Future Naval Defence based on the soft-kill methodology.

2.3

The false target generator must send different delay deception signals to adversaries at different distances

Could an InISAR simulator help create a deception system?

Part I - Chapter 2

Future Naval Defence Requirements

A countermeasure methodology in order to defeat a high resolution sensor with a softkill21 technique at a considerable distance from the friendly asset is the generation of false targets by stand-off expendable and autonomous decoy systems that would look to the approaching high range resolution sensor as a real target. Analytically for an adversary using an ISAR imaging instrument the false target needs to be made of coherent sequences of reflections with highly correlated amplitude and phase properties and proper delays. These signal properties must be transmitted simultaneously and appropriately for stand-off adversary surveillance platforms and fast-approaching tracking sensors. At all times the false target must disguise as a signal that would have come from the multiple scattering surfaces of an actual naval target at appropriate elevation and azimuth permutations to the appropriate inquiring sensor (11)[Balwindson,2007].

Current characteristic approaches are bespoke FPGA-based design (42)[Fouts, 2002], Current Off The Shelf (COTS) systems utilization (41)[Fouts, 2005] and scintillation generation based on pseudo random sequences (165)[US Patent 5532696].

The objective of this work is to provide novel means to the arsenal of Deception in Naval Defence. In this thesis it is proposed that an Interferometric ISAR simulator can be used for creating plausible proof of concepts regarding the study of false target images to high resolution radar systems.

The review of analysis of defence methods is shown in Table 2.1.

Deception in Naval Defence

23

Evolution of Reconnaissance, Firing and Soft-Kill Methods for Naval Targets World Wars Contemporary Future Observation Type: optical microwave microwave Sea Level and Aerial Observation Type: very low fre- very low fre- very low freUnderwater quency quency quency Firing Solution for human decision distant - computer far distant all mediums and sonobuoy as- computer and sisted sonobuoy assisted Firing Solution close distant far distant Distance for all mediums Camo grey to dazzle dazzle to grey grey to SdCS Patterns Ability to generate Generation of Generation of The SimulatorFalse Naval Targets false naval targets false naval targets defined Counterwas impossible was impossible measure Systems due to up close due to technol- (SdCS) Proposal optical obser- ogy limitations vation by the although ceradversary tain other decoy systems were available Table 2.1: Review of Naval Warfare

24

Part I - Chapter 2

From the analysis of Table 2.1 the real world question could be: Since the reconnaissance and targeting steps are made at a great distance could an InISAR simulator cloak a real naval target by injecting to the adversary sensors many verisimilar to the real targets in order to provide services of security by obscurity?

First Requirement

Second Requirement

Third Requirement

The answer to the InISAR proposal must be provided with a characteristic proof of concept. And a poignant proof of concept must be supported by a controlled experiment that allows its results to be readily verified and validated. In this case the first fundamental requirement of the controlled experiment must be the provision of different delay deception signals to adversaries that are located at different distances from the false target generator. Therefore a threat assessment scenario must be drafted in order to be able to support the above requirement for two common, characteristic and important cases. First a stand-off high altitude long distance reconnaissance platform that is moving away from the naval target. Secondly an approaching missile that has been fired from the stand-off platform and is rapidly closing on the false target generator. Moreover the second fundamental requirement is the verisimility enhancement of the false targets. The purpose of producing these overall results of increased verisimility effects with the above methodology is the effort to make the false naval targets more realistic to the adversary radar-operator (machine-human) system.

And the third fundamental requirement is the relation of computer networks warfare to the simulator-defined countermeasures design. Computer Networks Warfare and Electronic Warfare form the two parts of the domain of Information Warfare. It would be interesting to investigate the interconnection of these parts through this research.

2.4 Final Conclusions

Chapter Conclusions

This chapter firmly established the real world needs for revolutionary technological advances for naval soft-kill countermeasures. The next chapter will investigate the current state of the art in engineering that exists regarding the previously stated needs and set the foundations of what should be demanded by the military and academic communities.

Deception in Naval Defence

25

Sources & Facts 1 http://en.wikipedia.org/wiki/Kriegsmarine

Deutsche Kriegsmarine

2 http://en.wikipedia.org/wiki/Merchant_raider Schiff 41 or Raider G was a Han-

delsstoerkreuzer or Commerce Disruption Cruiser.

3 http://en.wikipedia.org/wiki/German_pocket_battleship_Deutschland Ger-

man battleship raiders sometimes had an american type of designation numbering written on their bows.

4 http://en.wikipedia.org/wiki/German_submarine_U-99_(1940) One of the most

successful U-Boots of the Second World War. 5 http://en.wikipedia.org/wiki/Q-ship

Q-Ship

6 http://www.imdb.com/title/tt0048990/

The Battle of the River Plate

7 http://en.wikipedia.org/wiki/Norman_Wilkinson_(artist)

Norman Wilkin-

son 8 http://www.history.navy.mil/photos/images/h51000/h51392.jpg

Off New

York City, 8 July, 1918.

9 http://www.merchantnavyofficers.com/cunard7.html

Gloire in horizontal daz-

zle.

10 http://smmlonline.com/articles/kriegsmarinecamo/kreigsmarine.html A

wide range of camouflage patterns ranging from a single color overall to complex multicolor dazzle schemes.

11 http://www.battleshipbismarck.com

KSM Bismarck dazzle pattern.

12 http://en.wikipedia.org/wiki/Battle_of_the_Atlantic_(1939-1945) Bat-

tle of the Atlantic 13 http://en.wikipedia.org/wiki/Enigma_machine

The ENIGMA machine was used by the German High Command to rely coded messages to submarine operations.

14 http://en.wikipedia.org/wiki/Wolf_pack German submarines converged to the point

of a convoy in order to conduct their attack, just like a wolf pack.

15 http://en.wikipedia.org/wiki/Submarine_snorkel 16 http://en.wikipedia.org/wiki/Fritz_X

Fritz-X.

Snorkel

26

Part I - Chapter 2

17 http://en.wikipedia.org/wiki/Heinkel_He_177

Heinkel He-177.

18 http://en.wikipedia.org/wiki/Dornier_Do_217

Dornier Do-217.

19 http://www.battleships-cruisers.co.uk/warspite.htm 20 http://en.wikipedia.org/wiki/Monopulse_radar

HMS Warspite

First introduced in 1943!

21 http://en.wikipedia.org/wiki/Countermeasure Countermeasures that alter the elec-

tromagnetic, acoustic or other signature(s) of a target thereby altering the tracking and sensing behavior of an incoming threat (e.g., guided missile) are designated as softkill measures.

Deception in Naval Defence

27

Internet References http://en.wikipedia.org/wiki/Leigh_Light http://en.wikipedia.org/wiki/Dazzle_camouflage http://en.wikipedia.org/wiki/Military_camouflage http://www.iwm.org.uk/upload/package/8/atlantic/index.htm http://www.shipcamouflage.com/warship_camouflage.htm http://en.wikipedia.org/wiki/SMS_Seeadler_(Windjammer) http://en.wikipedia.org/wiki/German_auxiliary_cruiser_Kormoran http://www.imdb.com/title/tt0036516/ We Dive at Dawn http://www.imdb.com/title/tt0052151/ Run Silent, Run Deep http://www.imdb.com/title/tt0082096/ Das Boot http://www.ausairpower.net/WW2-PGMs.html Dawn of the Smart Bomb http://www.imdb.com/title/tt0099810/ The Hunt for the Red October http://www.imdb.com/title/tt0082351/ Eye of the Needle http://en.wikipedia.org/wiki/Cryptanalysis The ability to read the presumed-secret thoughts and plans of others can be a decisive advantage, and never more so than during wartime. http://en.wikipedia.org/wiki/HX_convoys http://en.wikipedia.org/wiki/SC_convoys http://en.wikipedia.org/wiki/CU_convoys http://en.wikipedia.org/wiki/First_Happy_Time http://en.wikipedia.org/wiki/Second_Happy_Time http://www.usni.org/magazines/navalhistory/story.asp?STORY_ID=1439 The Battle that had to be Won http://military.discovery.com/tv-schedules/series.html?paid=52.15853.

115486.29895.6 Weapons Races: radar & Stealth, A Nugus-Martin, FremantleMedia and the Military Channel Production

28

Part I - Chapter 2

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But, the bravest are surely those who have the clearest vision of what is before them, glory and danger alike, and yet notwithstanding, go out to meet it.

- Thucydides, 2.40.3, c. 400 BC

3

Literature Review

An essential element in the strategy of conducting research is to establish the amount of previous knowledge about the current subject. This will form the foundations for further research, as stated in (37)[Ellis, 2008, p. 25](95)[Leedy, 2005].

3.1

The demand for a solution to the reinvented problem

A classic text that emphasizes the advancement of technologies in naval warfare is The History of the Peloponnesian War which was written by the Athenian General and Historian Thucydides22 . Even in these ancient times naval supremacy was a decisive factor in any confrontation (169)[Vlahos, 1998]. Moreover at ancient times all confrontations had to be conducted at relatively close distances. Nowadays long to far distance operations is an integral factor in a modern conflict and countermeasure activities must follow suit. With that in mind when the decoy signal is produced on-board the friendly asset it is called self-protection and when it is produced off-board it is called stand-off protection (61)[Hill, 1988]. Furthermore the large physical size in volume and weight of the electromagnetic spectrum countermeasure technologies up to the 1990’s demanded that the solutions were mostly of self-protection nature. Standoff protection was still performed by still large in physical size friendly platforms that were far away from the threat signal and the friendly asset.

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SdCS Phd Thesis 2009

30

Part I - Chapter 3

Conventional radar systems see a target as a collective point scatterer. Due to this fact conventional countermeasure techniques fall into two major categories: angle deception and range deception. In the first case an example is Inverse Gain Jamming. With this method the jamming function is performed by transmitting replicas of the adversary signal back to the hostile sensor. A strong replica when the illuminating signal is weak and vice versa either evens out the phases or over compensates the sensor producing either way the deception effect. With the second method an example is Range Gate Pull-Off (RGPO). The hostile radar concentrates on the target by placing a range gate of a few hundred meters around the target. Because it no longer looks for other signals it is termed that the radar has locked on the target. The RGPO method breaks the lock by making the hostile radar lose this gate thus producing the deception effect.

Both methods work for conventional radar systems and will not deceive a high resolution sensor (181)[Wiegand, 1991]. Both above countermeasure methods are applied to conventional radar tracking systems, like the monopulse method. The emerging engineering problem is that all above countermeasure methodologies are not efficient when the target is viewed by a high range resolution system either in stand-off mode or when mounted on an approaching missile platform equipped with a miniaturized high range resolution sensor (ISAR mode). It is the miniaturization ability that redefines the problem and demands an appropriate novel engineering solution.

Therefore for the radar field the problem of air defence at sea needs to be re-invented for there is a need for direct ISAR countermeasures that would oppose a miniaturized high range resolution radar sensor. This literature review focuses on conventional ISAR simulators and then on coherent deception techniques in order to be able to draw beneficial information and build the foundations of the project work.

3.1.1

ISAR Simulators

Earlier studies by (150)[Shillington et al, 1991] have described a technique used to simulate ISAR images of a ship model while under angular motions such as yaw, pitch and roll. [Porter et al 1994] have presented the theoretical analysis of SAR techniques as can be applied to ISAR imaging of ship targets. Emphasis is given in the exploitation of information resulting from the point spread function. Also foundations are laid

Literature Review

31

towards the study of interference effects (glint). (59)[Haywood et al, 1994] have introduced the ISARLAB software package which is a comprehensive set of functions that emulate the particular functions of an ISAR system. And (38)[Emir et al, 1997] have developed a simulation program which can generate ISAR images of ships. The method is based on the localization of dominant scatterers and has applications in evaluating the performance of automatic ship classifiers. Recent studies by (183)[Wong et al, 2006] have clearly presented the mathematical basis of the Inverse Synthetic Aperture process. (100)[Ling et al, 2006] have investigated the acquisition of top or side view ISAR images with the proper cross range scaling. The technique is based on the measurement of slopes of the two main feature lines of the ship, which are the center line and the stern line. This process has the advantage of using only the acquired image to complete its tasks. (104)[Lord et al, 2006] have investigated methods to obtain three dimensional radar cross section (RCS) images using the ISAR concept. Results are provided towards the degradations effect of specular multipath effects on the final image. (133)[Rice et al, 2006] have described a method of ISAR image classification based on a comparison of Range-Doppler imagery to existing three dimensional ship reference models. This technique uses a sequence of ISAR images in order to estimate the dominant ship motion. In all above indicative work there is no mention of the computing force that provides the motion of the radar and target platforms. Our work makes an attempt to fill in the details of an ISAR simulation analysis in a virtual reality environment which is supported by a software defined radar system.

3.1.2

Coherent Deception Techniques

Using a simulator in the context of a software defined radar system falls under the coherent deception electronic attack technique. In this manner multiple targets can be generated which must have features nearly identical to the real ship target. And in order to ensure correct geometry and realistic false target velocities there is a need to take into account an estimation of the range, velocity and heading of the threat signal, as stated in (11)[Baldwinson, 2008]. From (187)[Yuan] it is concluded that is is beneficial to implement the false target signal entirely algorithmically. The purpose of the research is to obscure the real target into a cloud of other plausible yet false targets as stated by (142)[Rui]. The analysis in (184)[Xiaohan] states that the fake target mask,

32

Part I - Chapter 3

which are mainly coordinates and backscatter intensities, are stored in advance and that the Doppler”s slope is important in the deception imaging process because it helps the threat signal to focus on the false target. We address this point in our simulations.

Further false target geometry explanations can be found in example in (138)[Rongbing, 2007] where a geometry and signal model is presented. For an ASIC (application specific integrated circuit) approach (41)[Fouts et al, 2005] have implemented the first documented hardware-based complete false target generator system. Nevertheless the exact contents of the look-up table that synthesizes the target are not fully discussed.

3.2

Chapter Conclusions

The overall aims of this project are now clearer because:

∙ It was shown in Chapter 2 that there is a need23 for an engineering solution to the problem of coherent countermeasures. ∙ And here in Chapter 3 it was proven that there is a high demand for an effective and prevalent solution to satisfy the above mentioned need. Analytically the study of the related literature review proved that the concept of using a simulator for countermeasure purposes has not been fully investigated, related proof of concepts and system prototypes do not currently exist and therefore this project is indeed a new contribution to knowledge. ∙ Finally it was deemed that the employment of a proof of concept in order to begin the project investigation is indeed an effective and prevalent solution provider of electronic countermeasures for a modern extended naval target.

The following task in the next chapter is the drafting of competent requirements that would produce the best economically suited methodology in order to fulfill the aforementioned aims.

Literature Review

33

Sources & Facts 22 http://en.wikipedia.org/wiki/History_of_the_Peloponnesian_War Thucy-

dides 23 http://www.thefreedictionary.com/need

Need Definition

34

Part I - Chapter 3

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Part II Simulator-defined Radar Countermeasure Systems: Implementation Methodology Proposal & Results

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That evening Themistocles attempted a spectacularly successful use of tactical misinformation sending his servant Sicinnus to Xerxes with a message that he was "on the king’s side" and it would be best for the Persians not to let the Hellenic Navy escape from Salamis at nightfall.

- The Battle of Salamis, c. 480 BC

4

ISAR Simulator Implementation for Electronic Warfare

The simulation engineer of the false target generator system must first consider the domain and functional verisimility requirements. Then the simulation engineer must avoid the pitfall of not conducting extensive conceptual modelling of the final product.

In this case this task must be performed for both the false naval target outcome and for the important added effects for reality replication on the adversary ISAR display. Only then the implementation procedures must begin to be coded.

4.1

ISAR Countermeasures Requirements Engineering

When Themistocles designed his tactical misinformation act he must had been in deep thoughts of how the verisimility level of his stratagem would be raised in order to convince his adversary counterpart, King Xerxes. The answer came in the name of Sicinnus24 who, according to Plutarchos, was of Persian nationality. What better way to talk around your adversary than by employing one of their own people to set up your entrapment plan.

In the case of this project the verisimility levels must be raised in order to combat airborne Inverse Synthetic Aperture Radar systems. Because their sensors provide excellent surveillance, tracking and even fire-solution abilities for naval targets from a

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SdCS Phd Thesis 2009

38

Part II - Chapter 4

very far distance. Considering this serious maritime surveillance threat the simulation engineering solution demands for a simulator system that can be used to synthesize multiple false targets that would appear as credible military naval targets.

The simulation engineer of the false target generator system must first consider the domain and functional verisimility requirements. A requirement is defined as a necessary attribute in a system, a statement that identifies a capability, characteristic, quality factor of a system in order to be able to perform its intended functions (185)[Young, 2004, p.1]. It is a property that must be exhibited in order to solve some real-world problem (1)[SWEBOK, 2004]. Requirements are the basis for all the work to be done on the implementation of the final system (185). Real requirements are those that reflect the verified needs of users for a system. Developers know what to build. In the software quality sector the use case depicting the proof of concept requirements will be shown.

Software Requirements Specifications (SRS)(94) Investigate methods in order to achieve the drafting of correct requirements without the need for change. This white paper advocates the usage of simulations in order to elicit and validate requirements that seems promising (18)[Borland, 2009].

An organisation’s understanding of a potential system’s requirements prior to any actual design or development work. States required constraints. Functions as a blueprint for completing the project as economically as possible. Contains functional and nonfunctional requirements only.

The system description depicts the relationship between the inputs, transfer functions and outputs of the software system that resulted from the requirements draft process.

∙ Provides feedback to the customer ∙ Decomposes the problem into parts (components) ∙ Determines the input, transfer function and output of the system ∙ Serves as a verification and validation compass tool

ISAR Simulator Implementation for Electronic Warfare

4.1.1

39

End-User Requirements

An initial requirements engineering investigation reveals two major scenarios. First an actual friendly naval asset that needs tactical soft-kill protection. Secondly a decoy platform that can create a ghost fleet in order to spread strategic doubt to the adversary.

These points are accented as:

∙ Tactical: The simulator system shall hide actual friendly assets in a cloud of obscurity consisting of similar false targets. The actual naval target will thus be visible in adversary ISAR screens but scrambled in between the false entities.

Can lead to miscalculated targeting by the adversary. ∙ Strategic: The simulator system shall create ghost fleets with a special platform that is envisioned to be able to fly, float and submerge. Can lead to adversary confusion and waste of resources in a most vital moment of battle.

4.1.2

Verisimility Requirements

Fine tuning these scenarios with verisimility engineering issues in mind the refined requirements become as follows:

∙ Requirement 1: The resulting electromagnetic signature synthesis shall allow the implementation of returns that appear to backscatter from areas of high reflectivity as arranged in military superstructures instead of their commercial superstructure counterparts. ∙ Requirement 2: All false targets shall be able to move in a verisimilar movement through time progression. ∙ Requirement 3: Sensor error effects, like angular glint which is representative of naval extended targets, shall be copied to the false target entities. ∙ Requirement 4: The project shall have a code name that will allow easy identification. In this case the project’s codename is FB-16.

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Part II - Chapter 4

The research challenge is how useful, economic and straightforward it would be for the FB-16 ISAR simulator to support a software defined radar system in order to perform electronic warfare functions.

From the literature review of the previous chapter it was deducted that past and present engineering efforts tend to create ISAR simulators that want to depict the ISAR process. The focus of this work is the creation of false military naval target verisimility requirements engineering.

The main research effort is the attempt to establish the fact that an ISAR simulator can be used as a software-defined radar system in order to perform coherent countermeasure activities. For that reason an ISAR simulator is implemented in this work which addresses the reflectivity solution of an extended naval target as seen by an airborne high range resolution sensor (77)[Kostis et al, 2005] (78)[Kostis, 2006], (79)[Kostis, 2007], (80)[Kostis, 2008]. The design could easily be extended to accommodate an added value which is a glint effects generator (81)[Kostis EUSAR, 2008] (82)[Kostis et al, PCI2007]. For ISAR countermeasures purposes we argue that by injecting glint effects in the digital signal processing process the simulator can now produce more realistic results (83)[Kostis, 2008]. This added value is necessary in order to add realistic effects to the false target as stated by (118)[Neri, 2007].

For this value added process there are two methods of creating angular glint, Poynting vector and phase gradient.

The first method is discussed in (27)[Chen, 2008] where glint is calculated by the deviation of the Poynting vector and the heading vector. The second method is discussed in (112)[Ming, 2003] where and RCS (radar cross section) based compensation method is presented. For our purposes we have used the approaches found in (146)[Schleher, 1999] and (151)[Shirman, 2002] where they base the glint estimation on the transversal component of the interconnecting vector between the two interfering sources.

The threats are equipped with high resolution microwave (radar) sensors that are capable of resolving the ship target in slant, cross and even height ranges while always tracking their most prominent points. Relevant effective soft-kill methods, which means deceive rather than destroy, is the capture of the threat signal in digital radio frequency memory, its down-conversion, its injection with false target reflectivity data

ISAR Simulator Implementation for Electronic Warfare

41

by digital signal processing means, its up-conversion and final re-transmission to the threat sensor (118)[Neri, 2007].

The major contribution is the provision of an Interferometric Inverse Synthetic Aperture Radar simulator which can generate realistic false target effects by adding glint noise to the false target reflectivity solution. The threat signal always tries to compensate for this noise as it is an inherent characteristic of an extended target.

4.1.3

Domain Requirements

The domain engineering explains or describes the actual properties of a subject matter that can be partially or totally represented by a mathematical model and relevant computer code (15)(Bjorner, 2006, p. 8). Here the focus is in coherent jamming where the intention is to present many false yet plausible targets to the threat signal so the adversary radar-operator loop cannot differentiate between the friendly assets and ruse of war. For the naval scenario the friendly asset is an extended target which means that there are several points on the ship’s superstructure that backscatter the threat’s signal which in turn is received and processed by an Inverse Synthetic Aperture Radar (ISAR) system. It is only necessary to synthesize a false target that has almost the same radar cross section, or electromagnetic signature, to the protected friendly asset (11)[Baldwinson, 2008]. Therefore the false target must seem to be a collection of points dispersed in slant, cross and height ranges situated in a three-dimensional worldspace (118)(Neri, 2007). And to ensure correct geometrical properties and realistic false target velocities the range, velocity and heading of the threat signal must be taken into account (146)(Schleher, 1999). The false target entity properties must always be adjusted to the threat entity characteristics. The conceptual model for the domain engineering aspect is depicted in Figure 4.1. This figure is inspired by (129)(Pidd, 2004).

The main requirements for the radar case were that the countermeasure system shall: ∙ accept as input an extended naval target with reflectivity and phase at t = 0. ∙ utilize the transfer function I that provides a database of time delays (phase shifts) from t = 0 to t = τ (duration of operation).

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Part II - Chapter 4

Figure 4.1: Domain Conceptual Modelling

ISAR Simulator Implementation for Electronic Warfare

43

∙ utilize the transfer function II that provides the necessary transformations and preparations of the phase shifts (range-Doppler process for two-dimensional imaging) for transmission to the propagating medium( atmosphere). ∙ provide as output a database of properly prepared data for high range resolutions radar systems security by obscurity countermeasure functions.

4.1.4

Functional Requirements

The input determines the type of data that will be processed by the pace engine. The output block will determine the final shape of the input data.

The basic elements of the SdCS are

∙ the input data ∙ the pace engine ∙ the output module

Input(t − τ) = Input × Pace Engine

(4.1)

SdCS(t − τ) = Input(t − tau) × Out put Module

(4.2)

T M3 :

T M4 :

Assumption: the observable scatterers are in fixed positions on the target so that their motions are determined by the target as a whole.

44

4.2

Part II - Chapter 4

Conceptual Modelling I: False Naval Target Generator

The conceptual model for this simulation is constructed by considering standard representation theory. The modelling approach follows standard abstraction degrees for the three-dimensional synthetic environment, target fidelity and inverse scattering. The pace engine that acts as the computing moving force for the simulation is mathematically presented. The inverse scattering signal follows standard ISAR theoretical guidelines.

The data exchange standard between the various elements is presented. Issues in implementation and project success are discussed by drawing upon the verification and validation analyses.

The Conceptual Model deals with the context of the representation and the methodology that will be later followed in a concise and structured manner. A set of operations is comprised as a toolkit, called FB-16, in order to capture the representation and methodology issues that can be utilized to transform the initial states and resources of the input and produce a proper output using the FB-16 toolkit as the transfer function.

Attention is paid to specific constraints that govern the realm of ISAR Imaging in order for the output to be realistic. This is important because we aim to use the outcome of the project in order to recreate a realistic target as seen by high-resolution electromagnetic eyes (80)[Kostis, EUROSIM 2008]. In order to determine the final draft of the Conceptual Model there are five steps that have to be completed: Related Work Review (RWR), Application Domain Definition, Problem Space Decomposition, Entity Abstraction Degree and finally Entity Relationship Identification (119)[Neugebauer, 2007].

4.2.1

Application Domain Definition

The task of Application Domain Definition is given to the Subject Matter Experts that have authoritative information about the actual situational context. Usually at this point in time the Subject Matter Experts will hold several meetings with the Simulation Engineers and discuss the theoretical and practical milestones that have to be observed

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45

during the course of the project. Usually at this stage the Simulation Engineers will have only superficial knowledge about the subject matter. On the other hand Simulation Engineers that can perform the task of Subject Matter Experts are valuable for any particular situation.

The operational abilities are now explained of High Range Resolution radar systems by presenting a short relevant theoretical background. The main theoretical aspects for ISAR imaging are in order of logical progression : SAR imaging, spotlight mode of SAR imaging leading to ISAR imaging.

A SAR system has an antenna aperture which is synthesized by the combination of relatable parts rather than the real dimensions of its physical antenna. The SAR imaging principle is based on two foundations :

∙ Coherence25 . The standard relationship between the waves of an electromagnetic radiation beam. The effort of the radar system is to preserve the phase of the incoming signal. ∙ Sampling26 . The digitisation of continuous processes. The synthetic array is made up in a radar digital signal processor.

The major advantage of SAR systems is enhanced slant and cross range resolutions.

A numerical example will be utilised to illustrate all the above in mathematical terms.

Starting with a conventional 10GHz radar with an antenna aperture of 3 meters looking down to a target 10 Km away, the cross range resolution is :

CONV RES :

∆x =

0.03 λ = 10000 = 100m d 3

(4.3)

This azimuth resolution is very low because a single resolution cell is illuminated at any one time. For example two ships less than 100 meters apart at the same range would appear as only one echo. The system that was used in Pearl Harbour and rumoured

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Part II - Chapter 4

Figure 4.2: Conventional Radar Antenna

Figure 4.3: Phased Array Antenna

ISAR Simulator Implementation for Electronic Warfare

47

to have detected the Japanese coming of aircrafts is such a characteristic early design radar, namely the SCR-27027 of Figure 4.2.

The naval target is chosen because it is the easier subject that can provide verified and validated results even by inspection of the generated data.

4.2.2

Problem Space Decomposition

The entities and processes that must be represented for the successful accomplishment of the simulation are defined. For this project the list of entities as shown in Table 4.1.

Now we can draw the necessary associations between the entities and come up with the corresponding processes, as shown in Table 4.2. Again as above the comparison between the reality and the simulation is strongly taken into account.

4.2.3

Entity Abstraction Degree

The representational abstraction of the involved entities is finalized in this step. The level of accuracy, precision, resolution and fidelity of the entities and processes is determined. For this project the level of aggregation should involve a target that is made out of one-hundred and forty-five points. The ISAR system will be mainly operating at 5 GHz with a Pulse Repetition Frequency of 1KHz. Other operational values can easily be accepted by the simulator.

4.2.4

Entity Relationship Identification

The relationships among the entities are identified in this design phase. It is ensured that all constraints and boundary conditions are properly imposed by the simulation context. All operational and functional requirements are taken into consideration, as shown in Figure 4.7.

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Entities 1

2

3 4 5

6 7 8 9

Simulation Target Cartesian coordinates plus inherent amplitude and phase Radar slant range and cross range Cartesian coordinates with respect to the center of the target

Reality Target physical properties and electromagnetic signature

Most prominent appears to be the middle of the ship for this project. But it could be in the stern or the bow of the ship.

Sea-level distance from radar to FM height finder radar (altimetarget ter) on airborne platform Radar operational parameters ISAR system specific functions Aspect angle from radar to target Change of aspect angle from radar to target provides the resolution acquisition process Glint Effects Physical Phenomenon Pace Engine Target movement due to forces of nature ISAR processor details Range-Doppler processing ISAR system output Slant Range Profile and ISAR Image of target Table 4.1: Electronic Warfare Entities

4.3 4.3.1

Conceptual Modelling II: Angular Glint Enhancement Application Domain Definition

There are three distinctive airborne threats to a naval target that current air defence at sea countermeasures are called upon to address in the modern era (61)(Hill 1988). The revolutionary threat of Unmanned Airborne Vehicles (UAV) carrying out surveillance tasks (67)(Jane’s 2005), the contemporary threat of sea skimming anti-ship missiles launched from near sea level aircraft (Chant 2001) and the daring threat of low aircrafts flying over the sea level in an intercept mission to their target are proved by the

ISAR Simulator Implementation for Electronic Warfare

A

B

C

D

E F G H I

49

Processes Simulation Reality Provide information to the Pace En- Physical presence and movement of gine of target Cartesian coordinates to target the pace engine Provide information to the Pace En- Physical presence and movement of gine of radar two-dimensional (slant radar ranger and cross range) coordinates Provide information to the Pace En- Measurement - captures reality with a gine of radar’s third (height range) di- sensor mensional coordinates Provide information to the ISAR Pro- Instrumentation: operational informacessor about the radar�s operational tion parameters Aspect angle variation Caused by changes in target/radar location Glint Effects Injection Digital Signal Conditioning (Masking) processing From Pace Engine to rotated points Caused by changes in time database From Pace Engine Database to ISAR Recording Process: processes history Processor of target in computer memory From points database to ISAR proces- Computer process: Range-Doppler sor Processing - translates reality to computer memory Table 4.2: Electronic Warfare Processes

Falklands conflict (159)(Stavropoulos, 2008b). Glint generation for these characteristic threats to a naval friendly asset were examined in order to conduct a complete experiment, as shown in Figure 4.8.

All above threats are provided with high resolution sensors capable of spatial diversion.

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Part II - Chapter 4

Figure 4.4: ISAR Theory

4.3.2

Problem Space Decomposition

This work falls under the field of the soft-kill methodology where the friendly asset is trying to deceive and evade the threat rather than by directly destroying the aggressor force. With this method the threat signal is down-converted by the reception subsystem, then stored in digital radio frequency memory where its operation parameters are analysed and a false target is created. In this work this false target reflectivity data is injected with glint effects by digital signal processing means, then up-converted and final re-transmitted to the threat sensor (118)(Neri, 2007). This is the reason that the emphasis is on the False Target Generator Subsystem, as shown in Figure 4.9. At all times the false target must disguise as a signal that would have come from the multiple scattering surfaces of an actual naval target at appropriate elevation, azimuth and most importantly distance permutations to the appropriate inquiring sensor.

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Figure 4.5: General Depiction of a High Range Resolution Process

4.3.3

Entity Abstraction Degree

The level of entity abstraction degrees of the target and the simulation geometry are now defined.

Using the right amount of Complexity the Simulator Extensibility Task I is now explained, which is the effort of forging an appropriate target abstraction Degree The target map for the glint case is shown in Figure 4.10. There are two isotropic scatterers within each resolution cell and each reflector is characterized by its polarization profile for wideband illumination by a monostatic radar. In other words there is an initial amplitude and phase to each scatterer that is particular to the specific viewing parameters. For the scatterers that lie in the x-axis the initial amplitude is 1 and the initial phase is 0. Therefore these points are set up to be the most prominent scatterers within their corresponding resolution cell. The interfering scatterer is added with initial amplitude values that range from 0.1 to 0.9 while their initial phases range from 0 to 359, as shown in Table 4.3.

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Figure 4.6: ISAR Geometry

ISAR Simulator Implementation for Electronic Warfare

Figure 4.7: Entity-Relationship Identification

Figure 4.8: Strategic tasks with expendable ISAR capable decoy systems

53

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Figure 4.9: The position of the false target generator subsystem.

Figure 4.10: Target Map

ISAR Simulator Implementation for Electronic Warfare

Cell ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Prominent Point 003 008 013 018 023 028 033 038 043 048 053 058 063 068 073 078 083 088 093 098 103 108 113 118 123 128 133 138 143

Interfering Point 009 002 019 012 029 034 027 044 037 054 047 064 057 062 079 072 089 094 087 104 109 102 119 124 117 122 139 144 137

55

A

φ

0.1 0.1 0.3 0.2 0.2 0.25 0.4 0.3 0.3 0.6 0.35 0.8 0.55 0.8 0.7 0.8 0.8 0.6 0.8 0.2 0.2 0.2 0.1 0.5 0.1 0.5 0.1 0.1 0.15

0 45 135 45 270 0 180 0 0 45 315 0 90 0 20 0 90 315 90 315 0 135 0 180 0 0 0 0 45

Table 4.3: Reflectivity Solution Values per Resolution Cell.

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Figure 4.11: Glint Geometry

Now the input requirements to the simulator are completed. Analytically the target abstraction degree corresponds to the middle axis of the target. For a commercial application many more layers identical to this process would be required.

The simulation geometry abstraction degree is shown in Figure 4.11.

ISAR Simulator Implementation for Electronic Warfare

4.3.4

57

Entity Relationship Identification

The relationships among the entities are defined in this design phase. All operational and functional requirements are taken into consideration, as shown in Figure 4.11.

4.4

Implementation Procedures

This project utilised the following design concepts: ∙ Entity-Relationship Modelling for ISAR Processing. Every layer that corresponds to a target reflectivity layer solution is supported by a valid function that can be stored in a database system. First a function is launched that creates the Three-Dimensional Single Layer Extended Target Modelling. This solution corresponds to the highest superstructure height. In order to increase the verisimility of the false target the effert continues with the Three-Dimensional Multiple Layer Extended Target Modelling. This solution provides intermediate reflectivity solutions just like a real ISAR image.

∙ Naval Target Platform Increased Complexity Approach. First a Parallelogram Model is made in order to provide verification and validation by visual inspection. Then a More Model is used that utilises only local reflectivity of the target.

The final target abstraction is the More Detailed Model which combines local and distance induced phase differences in the false target ISAR image.

4.4.1

Synthetic Environment Abstraction

The important detail is that the geometry setup must be centered on the false target. In this case the origin is declared when the center of gravity and the center of buoyancy are co-located on the z-axis (34)[Doerry, 2008, pp.11], (179)[Watson, 1998] in other words when the ship is upright, as shown in Figure 4.

The foundations must be formally dictated by Cartesian geometry (134)[Rich, 1989].

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Figure 4.12: Single Layer Model System Design

4.4.2

Entity-Relationship Modelling for ISAR Processing

High Range Resolution Systems utilise numerous resolution cells that divide up the target into several blocks. From each of these blocks information can be extracted that can tomographically describe the nature of the target. Particularly in a resolution cell the radar can resolve features that belong to the same x and y coordinates but have different height values. For the simulation of this situation a multiple scatterers target model, which is also called extended, is required. The emulation of the aforementioned situation can be based on database modelling, using the entity-relationship model for the single layer target as shown in Figure (4.12) and the entity-relationship model for the multiple layer target as shown in Figure (4.13).

The main difference is that in the first model only one return is received by the radar per resolution cell whereas in the second case there are multiple returns from the superstructure, always per resolution cell, since many reflectance points are simulated.

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59

Figure 4.13: Multiple Layer Model System Design

4.4.3

Three-Dimensional Single Layer Extended Target Modelling

It is assumed that the radar sensor can divide the vessel into one hundred and forty-five (145) square equal cells. Each of these cells produces an echo back at the radar which is modelled as a complex number (amplitude and phase), as described in Equation 4.4.

Q(~k) =

Z

2(~k ~x) j

I(~x) e

Z

d~x

I(~x) =

~ q(~k) e−2(k ~x) j d~k

(4.4)

Analytically each cell is characterised by a reflectance amplitude and an initial phase associated with the corresponding scattering point (74)[Knott, 2007], as represented in Equation 4.5.

RESOLUT ION CELL = Ae jφ

(4.5)

where A is the Reflectance Amplitude and φ is the Reflectivity Initial Phase of the resolution cell on the target. All resolution cells form the complete reflectance model which is shown in Figure 4.16 and Figure 4.17.

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Part II - Chapter 4

Figure 4.14: Higher reflectivity on higher superstructure only

A characteristic of military naval targets is high reflectivity on lower superstructure coordinates and mainly on the deck levels.

4.4.4

Naval Target Platform Increased Complexity Approach

The increased complexity approach followed for this project involved the employment of a simple model that initially looks like a cube and then evolves into a full-fledged battleship superstructure.

4.4.4.1

Parallelogram Model

The first target used was a cube target which when viewed by a high range resolution radar system produces a parallelogram effect.

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61

Figure 4.15: Higher reflectivity on deck levels

4.4.4.2

More Model

The simple model consists only of the points that comprise the higher superstructure, with double-trip range delays.

4.4.4.3

More Detailed Model

In order to increase the verisimility of the false target the ISAR image must be filled in just like the real equivalent.

4.4.4.4

Multiple Deck Model

Reusability allows the creation of the Multiple Layers Addition into the simple model.

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Part II - Chapter 4

Figure 4.16: Higher Superstructure

ISAR Simulator Implementation for Electronic Warfare

Figure 4.17: Deck line and middle superstructure

63

64 4.4.4.5

Part II - Chapter 4 High Reflectivity on Lower Superstructure

High valued reflectors in lower superstructure height will distort the shape of the ship, as the shape corresponds to a large degree to the battleship’s silhouette but is actually a measure of the electromagnetic backscatter emanating from the superstructure.

Therefore it should never be confused with the physical dimensions of the target. In other words the Range-Doppler method will exhibit higher reflectance on parts of the target that may be gun placements or antennas, leading to a purely microwave type of observation (78)[Kostis et al, 2006].

4.4.5

Glint Effects Addition

The model and simulator can easily be extended to provide for other aspects of radar high resolution imaging.

Since a dominant characteristic of extended naval targets is the angular glint phenomenon as stated by (149)[Siouris, 2003, Section 3.4.2 Missile Noise Inputs, pp.

113-115], the work presented here is the study of injecting angular glint effects to a ship target’s upper superstructure. In this manner the ship’s superstructure seems corrupted by angular glint noise which corresponds to distance displacements of these points in appropriate (correct) sides of the superstructure depending on where the interfering scatterer is located.

4.4.6

Module Interconnection Language

The module interconnection language depicts the structural design of a system. In other words it shows the way the modules that comprise the system are interconnected.

An important factor in this field is the form of the information that is exchanged between the modules. An example of the internal structure of an input packet is shown in Figure 4.18(a).

The expectations of a model are usually a trial and error experience, as stated by (99)(Lieberman 2007, p.13). This statement is also true in the implementation of the

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65

structural design of the system. For example during the construction of this project it was found that by forming the output of any transfer function by the intact input packet plus the new output information there is a considerable speed and convenience in the realization of a functional proof of concept. All new information is always added to the left side of the output packet, as shown in Figure 4.18(b). Analytically the realisation of the proof of concept is speeded up because the packet structure is rich in elements that can be used by diverse transfer functions. For example suppose a subset of elements is used from packet A, as shown in Figure 4.19(c). This results in the output packet that is comprised by packet A and packet B. Using the newly crafted packet through transfer function 2 results in a new packet, as shown in Figure 4.19(d). This is a normal flow of implementation towards the structural design of the system. The power of this MIL methodology is shown in Figure 4.19(e). Here transfer function 2 was deemed not appropriate for the task at hand and the following actions needed to take place:

∙ More elements of the input packets needed to be engaged. ∙ The transfer function needed to be rewritten.

It may seem as a paradox to craft such large packets, but now it is evident that this methodology of reinserting the input packet to any output results in rapid implementation times. Because the designer is not distracted by the input structure in the case of a need to change any transfer function of the system.

The adoption of a standard for the communication protocol between the input data, the transfer functions and the output of the project increases the possibility of a successful realization, as can be seen in (122)[OTA-BP-ISS-136, 1994]. For this project the propagation of information between the system blocks has a custom made form. There are three main advantages. First it is easy to work through the creation and compilation phases of implementation without having to learn a current protocol. Then debugging is easier to conduct because the authors had full control during the creation process.

Finally in this manner it is much easier to upgrade and extend the system thus making it able to easily adapt to future demands. An example of a packet structure that is used is presented in Figure 4.18.

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Part II - Chapter 4

Figure 4.18: Packet breakdown analysis (sample)

Packets are declared as either input or output. The slots of the packets are strictly assigned to the corresponding kind of information. For example slot 2 in an input packet can never be anything else than a slant range parameter of a scatterer. The next step is the translation of the above graph into the corresponding information propagation model that the computer simulator can understand, as shown in Figure 4.19.

ISAR Simulator Implementation for Electronic Warfare

Figure 4.19: Module Interconnection Language (MIL)

67

68

4.4.7

Part II - Chapter 4

Pace Engine

The pace engine is the computing moving force that proceeds the points on the ship in time to new locations from their initial values depending on the (ordained by the Subject Matter Experts and the Simulation Engineers) motion of the ship. Therefore the movement of the target can be represented by a dynamical system. Modelling of the Pace Engine is done by utilizing the theory of affine transformations, whereby a three-dimensional point on the ship is multiplied by appropriate 4 by 4 matrices that provide motion effects, as explained in an excellent descriptive manner by (2)[Abrash, 1997]. For example a point in a three dimensional plane represented by a 4 by 4 matrix is multiplied consecutively with other 4 by 1 matrices that perform roll, yaw, pitch and translational transformations in space so to produce new motion coordinates in 3D space that can be easily translated into 2D space. This transformation is necessary because the ISAR process has a two-dimensional outcome. In order to explain this in a better way we use an example of a 4 by 4 matrix approach used in order to pitch the target into time (2)[Abrash, 1997] (75)[Kolman, 1986].

By multiplying the transfer function matrix with roll, depression angle and aspect angle matrices we can perform any motion possible by a ship vessel. An important point must be raised here by considering that translational motion does not play a major part in ISAR imaging and should be treated in this manner. We defend the above approach and provide for the translational motion of the vessel because we claim that we can lay the foundations for a false target generator system. Such a generator should be able to move the false ship target into space and therefore we consider the furnishing of translational motion to be of great importance in our case.

The complete mathematical solution is shown in Equation 4.6 in full form and in Equation 4.7 in block form. The contents of the movement permutation matrix are outlined in Equation 4.8.

Respectively the aspect angle and depression angle matrix is given by Equation 4.9, the roll matrix is shown in Equation 4.10 and the pitch matrix is given in Equation 4.11.

ISAR Simulator Implementation for Electronic Warfare 4.4.7.1

69

Roll Motion

In this work only roll motion is employed.

      x(new) cosθ 0 sinθ translationunitinx x(old) y(new)  0   1 0 translationunitiny     y(old) ML2 :  = x  z(new) −sinθ 0 cosθ translationunitinz z(old) 1 0 0 0 1 1

(4.6)

" # movement permutationmatrix t ML3 : ShipPosition(t) = 0T 1

(4.7)

ML4 : MovementMatrix = (AspectAngle)(RollMatrix)(PitchMatrix)

(4.8)

where,

The aspect angle - depression angle matrix is



 cosθ 0 sinθ   ML5 : Aspect − Depression =  0 1 0  −sinθ 0 cosθ

(4.9)

The pure roll motion matrix is



 cosθ 0 sinθ   ML6 : Roll =  0 1 0  −sinθ 0 cosθ

(4.10)

The pure pitch motion matrix is



 cosθ 0 sinθ   ML7 : PurePitchMotionMatrix =  0 1 0  −sinθ 0 cosθ

(4.11)

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4.4.8

Part II - Chapter 4

Inverse Scattering

The radar platform is characterized by the radar operational parameters: wavelength, type of modulation, transmission power and antenna aperture. These parameters can be set to many different values depending on the simulation scenario. The main point is the simulation of the range calculation between the radar and the target points as they move and rotate in the virtual worldspace. This digital world is described in Figure 4.20.

Figure 4.20: Digital World Implementation

The geometry follows well established and recent geometrical models in the field of ISAR imaging (126)[Pastina, 2008]. And for the ISAR calculations we have used the

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71

mathematical approach used by (50)[Given, 2005] (51)[Given, 2005] which is sound and fully describes the involved imaging mathematics.

Moreover for the target resolution cell calculation the modelling approach which can be found in (106)[Lynch 2006, p. 98] was followed. This method is called the CookieCutter footprint calculation. This is a simple way to represent the radar coverage of the target and is deemed adequate for this representation. The radar’s transmitted angle pattern is made to have an equal diameter at all the major beamwidth points of 3, 10 and 20dB. The resulting pattern is an elliptical cone in rectilinear space. Those cones offer the footprint which can be seen in Figure 4.21. This figure provides the emulation for the phased array antenna of the threat sensor.

Figure 4.21 is further discussed by stating that the resulting footprints are the outcome of the polar format algorithm usually implemented in conventional ISAR systems, as (24)[Carrara 1995, p.105] explains. The two-dimensional sampled data space encompasses samples that are stored in a polar coordinate form in the radar’s memory.

Moreover the spatial occupation of the received data is calculated using the small-angle approximation again as in (24)[Carrara, 1995]. This way the radar achieves its azimuth resolution which dictates the afore-mentioned data storage requirements.

4.4.8.1

Range-Doppler Process

The final step of the simulation is the way to represent the signal processing block after the receiving block, which usually is a Phased Array Antenna system. More information about phased array antennas are found in (172)[Visser, 2009]. After reviewing the theory of ISAR and phased array antennas the solution of the signal processing block representation is the division of the vessel into 33 resolution cells. Each cell contains the raw addition of the amplitudes and initial phases of the target with the phase delays that are added by the distance calculator block. The resolution cells are depicted in Figure 4.22. A similar explanatory figure can be found in (155)[Son Sok, 2002].

There are certain shortcomings related to the fact that the ISAR method is inherently dependent on the target’s changing its viewing angle to the radar (180)[Wehner, 1998, p.435]. First the cross range dimension scale is a direct function of the target’s aspect angular rotation rate. Second the ISAR image plane does not reveal the true aspect

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Part II - Chapter 4

Figure 4.21: Theoretical Implementation of Inverse Scattering (Polar Format Approximation)

of the target. And finally target dwell time required to produce a given cross-range resolution is dependent on the target’s aspect rotation rate relative to the radar.

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73

Figure 4.22: Range-Doppler Process

4.5

Chapter Conclusions

The conclusions from the discussion of this chapter are: The method of generating ISAR images for the purpose of generating false targets for electronic warfare purposes is described in this work which addresses both the simulation engineering and the radar engineering communities.

The threat radar and the friendly assets are moved while interacting into a three dimensional environment. The target returns are carefully crafted to realistic levels by considering ISAR imaging considerations.

The next task is to establish the quality factor of the software system. This is an essential step in order to check whether the constructed system mirrors the correct project purpose stated in the requirements.

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Sources & Facts 24 http://en.wikipedia.org/wiki/Sicinnus

Sicinnus

25 http://envisat.esa.int/handbooks/asar/CNTR5-2.htm

Coherence

26 http://users.ece.gatech.edu/~mrichard/FundRadarSigProc.htm 27

Sampling

http://en.wikipedia.org/wiki/SCR-270_radar SCR-270 Radar System

I know at sight what a position contains. What could happen? What is going to happen? You figure it out.

I know it!

- Hose Raul Capablanca, World Chess Champion, c. 1921

5

Software System Quality Factor

In this stage the Simulation Engineer must perform a quality factor process on the implemented software. The McCall’s software quality factor model is used which considers three main evaluation categories and these are operation, revision and transition. In order to assess the quality factor of the controlled experiment the element that must be assessed of each of these categories is correctness for operation, flexibility (expandability) for revision and reusability for transition.

5.1

Quality Factor Definition

Certainly Capablanca had quality in his chess gameplaying. Every play was modular, reusable and expandable leading to complete and reliable responses to opponents movements. In one word his actions were correct. The test of this correctness was his being the World Chess Champion for sever years.

Capablanca was part of an alive system, as defined by (166)[Unhelkar, 2003]. This chess human-pawn system completely satisfied the demands of the current situation (available arsenal of chess tactics and strategy) and the needs of the end user (victory).

In this project the demands of the system must be tested by appropriate verification and validation of the relevant computer code. And the needs of the end user will be said to be satisfied by the construction of an appropriate proof of concept that demonstrates in a correct manner the underlying principles of operation. This cobination will establish how good the countermeasure system is for the task.

University of the Aegean

75

SdCS Phd Thesis 2009

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5.1.1

Checklist of Software Quality Factors

∙ Correctness. The extent to which the software satisfies its specifications and fulfils the user’s objectives. Also the extent to which the software is fault free (i.e., free from design defects and from coding defects). ∙ Reusability. The extent to which the modules can be used in multiple applications. ∙ Reliability. The ability of the software to perform a required function under stated conditions for a stated period of time. ∙ Testability. The extent to which the software is easy to test to ensure that it performs its intended function. ∙ Accuracy. The precision of computations and control. ∙ Completeness- degree to which full implementation of functionality required has been achieved. ∙ Expandability- The ease with which the software can be modified to add functionality and the degree to which one can extend architectural, data and procedural design. ∙ Modularity- functional independence of program components.

Verification and validation tasks are further performed in order to determine the level of confidence or accuracy of the results created by the simulator. In this stage the reliability, reusability and extendibility attributes of the project are explored.

A verification and validation effort strives to ensure that quality is built into the software and that the software satisfies, in this case, the verisimility requirements (IEEE 1059/93).

Software System Quality Factor

5.2

77

Verification

Verification is a quality process used to evaluate whether or not a system complies with the initially stated algorithmic specifications, regulations and conditions. In other words it is the process that establishes the mathematical agreement of the final product to the physical phenomenon that it has been called upon to represent.

5.2.1

ISAR Module Verification

The method to verify the model involved the diversity in increasing complexity of the major mathematical expressions within each component (73)[Kleb, 2007]. Analytically the expressions that were refined towards better resolution were the range finder equation, the polarization properties, the signal attributes and the environmental response of transmit receive block and the digital signal processing block algorithm.

Therefore verification for this project is done at component level.

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Figure 5.1: Uniform amplitude/phase model, Model 1 (a) Slant Range Profile (b) ISAR image, Model 2 (c) Slant Range Profile (d) ISAR image

Software System Quality Factor

Figure 5.2: Diverse amplitude/phase single layer model with added phase delay effects, Single Layer (a) Slant Range Profile (b) ISAR image

Figure 5.3: Validation procedure

79

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Part II - Chapter 5

Figure 5.4: Simulation complexity history

Software System Quality Factor

5.2.2

81

Glint Effects Module Verification

The verification analysis checks whether the modelling process of the inverse scattering with angular glint was done correctly. In this manner the sensor is able to spotlight a target area and extract scene information by sampling with a three-dimensional Fourier transform of the radar reflectivity of the illuminated area (24)[Carrara, 1995, p. 99].

In order to translate this information to the two-dimensional domain the Polar Format Algorithm is engaged. The relationship between the three-dimensional data geometry and the two dimensional spatial frequency or wavenumber domain that is shown on the radar terminal is made via the wavenumber vector which is dependent on the unit vector along the instantaneous slant range vector , as shown in Equation 5.1.

~ = 2π 2~R K λ

GL1 :

(5.1)

This distance R is incorrectly estimated by the sensor as it approaches the target because there is a mismatch between the desired and the actual positions of the scattering centers. The reason is the poorly resolved elements per resolution cell that are produced by the phenomenon of Angular Glint .

Radar Angular Glint can be defined as the apparent displacement of the target from its actual position. The error is a displacement of the actual target centroid in distance.

Such an error is produced by a complex or extended target or when the reading at the seeker sensor exceeds or approaches the equipment error for the given coordinate measurements (151)[Shirman, 2002, pp.225]. Therefore this error needs to be incorporated into the false target imprint so the end result can look more credible to the system composed of the human element and the radar equipment. The distance between the two scatterers is shown in Equation 5.2.

GL2 :

L =

q (ui − vi )2 + (u j − v j )2 + (uk − vk )2

(5.2)

The midpoint length is

r GL3 :

Lmid point =

(

ui − vi 2 (u j − v j )2 (uk − vk )2 ) + + 2 2 2

(5.3)

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The midpoint vector is:

GL4 :

dmid point =

uj −vj ui − vi uk − vk i+ j+ k 2 2 2

(5.4)

dmid point Lmid point

(5.5)

The midpoint unit vector is:

GL5 :

dmid point =

The distance between the radar and the midpoint is: GL6 :

Lmid point = r (

uj −vj ui − vi uk − vk − RX)2 + ( − RY )2 + ( − RZ)2 (5.6) 2 2 2

The vector between the radar and the midpoint is:

GL7 :

Rmid point = (

uj −vj ui − vi uk − vk − RX)i + ( − RY ) j + ( − RZ)k (5.7) 2 2 2

The unit vector between the radar and the midpoint is:

GL8 :

Rmid point =

Rmid point Rmid point

(5.8)

The vector which is normal to the midpoint vector is found by taking the cross product of the unit vector between the radar and the midpoint and the midpoint unit vector is:

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T d~glint = ~Rmid point × d~mid point

GL9 :

(5.9)

It is assumed that the radar is tracking a prominent point which is the highest point in the middle of the superstructure. Any other point is found to yield the same results as in the real situation. Therefore the distance between the prominent point and the radar sensor is stated by the LOS variable

r GLA :

LOS =

(

ui − vi 2 (u j − v j )2 (uk − vk )2 ) + + 2 2 2

(5.10)

(

ui − vi 2 (u j − v j )2 (uk − vk )2 ) + + 2 2 2

(5.11)

Rmid point Rmid point

(5.12)

The line of sight vector is r GLB :

~ LOS =

And the LOS unit vector is: GLC :

Rmid point =

The angle between the transverse glint vector and the line of sight vector is given by the dot product of these two vectors is: GLD :

T ~ cosψ = d~glint ∙ LOS

(5.13)

The miss distance is calculated Rmiss by using the mathematical formula from (146)[Schleher, 1999, pp.269-270] is: GLE :

Rmiss

1 − A2 Lcosψ = 2 1 + 2Acosϕ + A2

(5.14)

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where, A is the ratio of amplitudes of the prominent and interfering scatterers (jamming sources) in the same resolution cell, ϕ is the initial phase difference of the prominent and interfering scatterers (jamming sources) in the same resolution cell, The glint generator mathematical module is now engaged in order to create the phenomenon of glint as stated above in each resolution cell of the High Range Resolution (HRR) sensor. The visual layout of the above process is shown in Figure 6.

The corresponding algorithm is shown in Table 5.1

ID 1 2 3 4 5 6 7

Type RADARXYZ PRMXYZ PRMY PRMAF INFXYZ INFAF trackpoint

8 9 10 11 12 13

R λ θ r PACE H

Algorithm - Input Stage Description Radar position in 3D space Prominent scatterers Cartesian coordinates set Prominent scatterers Cartesian coordinates set Prominent scatterers reflectivity/initial phase set Interfering scatterers Cartesian coordinates set Interfering scatterers reflectivity/initial phase set Most prominent point that the radar tracks (top middle of the false target) Sea level distance from radar to trackpoint wavelength aspect angle roll rate Pace Engine (affine transformations generator) Radar Height

Table 5.1: Glint Generation Algorithm - Input Stage

The corresponding transfer function algorithm is shown in Table 5.2

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Algorithm - TF Stage ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Description Begin main R equals trackpoint-RADARXYZ RX equals Rcosθ RY equals Rsinθ RZ equals HEIGHT V_RADAR equals (RX,RY,RZ) LOS is the distance between trackpoint and V_RADAR V_LOS is the (unit vector at trackpoint-V_RADAR) foreach point in PRMXYZ foreach point in INFXYZ do V_dmidpoint equals (PRMXYZ-INFXYZ)/2 V_Rmidpoint equals V_dmidpoint-V V_DTglint equals V_Rmidpoint cross product with V_dmidpoint CosψequalsVDT glint dot productwithV _LOS L is the distance between PRMXYZ and INFXYZ Rmiss equals (L cosψ)/2 multiplied by (prominent to interfering reflectivity/initial phase ratio formula) end Table 5.2: Glint Generation Algorithm - Transfer Function Stage

The corresponding output algorithm is shown in Table 5.3 ~ which is the T The weight of the verification lies in the representation of the vector dglint main estimator of the angular glint, as defined by (151)[Shirman, 2002, pp.224-228] and as shown in Figure 5.5. ~ is the transversal T The superscript of the nomenclature vector means that vector dglint component of the vector d~ which is joining the prominent and the interfering scatterer within each resolution cell.

The verification method of the model involved the increasing complexity of the major

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Algorithm - Output Stage ID 1 2 3 4 5 6 7

Output Description Type I Figure [PRMXYZ,PRMY+Rmiss] PRMXYZ,INFXYZ,R,θ Type II Figure [Rmiss,k],Ν , Rmid point, Rmiss Type III Figure [RESCELL,speed] RESCELL,history of angular glint per resolution cell with respect to the radar from t=1 to t=32 msecs using the PACE engine.

End main Table 5.3: Glint Generation Algorithm - Output Stage

Figure 5.5: Glint Geometry

mathematical and processing block algorithms. First we set the glint generator block to be inactive and observed that no glinted outputs were produced. This strengthens the verification degree because we verified that when the glint engine is set in inactive mode the result is expected to lie in a straight line which represents the actual positions of the target, as shown in Figure 5.6.

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Figure 5.6: Verification Task I - Glint module disengaged produces no distortion to the false target

Then only one resolution cell is selected to exhibit glint and found that the program is be able to perform this action, as shown in Figure 5.7.

Therefore at this stage there is a strong indication that the algorithm is behaving in the desired and predicted manner.

5.2.2.1

Three Dimensional Representation

The first module is inspired by (152)[Skolnik, 2001] and demonstrates the glint effect in a three dimensional synthetic environment with respect to the real target points. We

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Figure 5.7: Verification Task II - Glint module engaged at one point produces a single distortion to the false target

call this component Glint Effect in 3D at the target. The involved mathematics are x − axis, NEW − SLANT − RANGE = PREV IOUS − SLANT − RANGE GLF :

y − axis, (5.15) NEW −CROSS − RANGE = PREV IOUS −CROSS − RANGE + Rmiss z − axis, NEW − HEIGHT − RANGE = PREV IOUS − HEIGHT − RANGE

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Two Dimensional Representation

Distortion Relationship between Slant Range and Glint Error The second module is inspired by (14)[Barton, pp. 101-103] and depicts the glint effect in as seen from above the target by the radar. This Glint Effect in 2D component is x − axis, Rmiss GLG :

(5.16)

y − axis, Wavenumber(DoubleTrip) =

5.2.2.3

4π(2Rmid point ) λ

Rotation Vector Contribution

Mask Criterion by tracking the rotational Doppler rate of change The final module is used to investigate the effect that the angular error has on the velocity vector back at the received threat signal. This method is used in order to measure the factor of realism of the glint formula. The involved mathematics are

x − axis, RESOLUT ION −CELL − ID(1..29) GLH :

(5.17)

y − axis, Wavenumber(DoubleTrip) =

4π(2Rmid point ) λ

Therefore a mask is created in order to act as an arbitrator signal to the first stage of an ISAR simulator, as shown in Figure 14. This is the representation of the generated three-dimensional mask with respect to time. Similar work to this approach is shown by (97)[Li, 2003] where an algorithm is devised in order to detect three-dimensional motion in ISAR data.

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Validation

Validation is the process of establishing documented evidence that provides a high degree of assurance that a system accomplishes its intended requirements. The process involves accreditation actions like acceptance and suitability certificates that the system model is compatible with the physics aspects that was designed to implement.

Validation is an intuitive process that involves Subject Matter Engineers and external customers. The organization model should be validated and tested against known or physically expected results in order to ascertain its authority. The validation loop that was followed is shown in Figure (5.3).

5.3.1

ISAR Module Validation

The application of the above testing procedure for the Time-Domain (upper row) and the Frequency-Domain (lower row) results is shown in 5.4. Therefore validation for this project is done at system level.The validation phases of this project involved its presentation to the respective radar and simulation communities through conferences and prospective journal articles, where there it can be subjected to peer review.

5.3.2

Glint Effects Module Validation

Validation Analysis: Determining the relevance, significance and selectivity of the results A credibility metric is needed in order to ascertain the results of this work, as in (101)[Liu,2004]. The selected specific geometry (aspect angle) setup with respect to the ship’s x-axis at forty-five degrees, the interfering scatterer positions with respect to the aspect angle setup at ninety degrees and the pure roll motion of the naval target which produces side-view ISAR images of the target provide a controlled experiment environment that is typical and representative of the complete domain of ISAR imaging. The above experimental setup is chosen because the results can be validated in a straightforward and satisfactory degree by pictorial inspection. Other geometrical and motion permutations are difficult to validate in an easy manner and with great confidence. The credibility metric is further enhanced by examining the relevance,

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significance and selectivity of the pictorial representation of our results in order to validate our claim that the simulator is producing the glint effect. The critical thinking process 28 of using images as evidence is employed.

This process is threefold:

∙ Relevance: A figure is relevant to the claim if it can lead to evidence towards justification by clearly depicting all the claimed key ideas. ∙ Significance: A figure is significant to the claim if it can lead to evidence towards justification by providing a purposeful, focused and well-defined way from claim to justification. ∙ Selectivity: A figure is selective to the evidence leading to justification if it is able to depict an increased amount of information about the justification, for example if it can be representative, typical and supportive of the complete domain of the original claims.

The major claim is that the program successfully generates glint effects as dictated by the laws of physics, as explained by (146)[Schleher, 1999]. This major claim is supported by three types of figures that visually depict the results of the simulator.

∙ For the first graph the sub claim is that since glint effects are added to the target then the shape of the target should be distorted. ∙ For the second graph the sub claim is that since the double-trip wavenumber is depicted then the glint effect as seen by the threat should be shown as a distortion of the arriving wavefront, as stated by (14)Barton. ∙ For the third graph the sub claim is that since the target was initially set at a pure roll motion then a side-view image of the target should be created, as stated by (135)[Rihaczek, 1996, Section 5.1.2.3 Roll Images, pp. 441-444]. This would show the degree of the glint effect as the high resolution sensor approaches the target.

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5.3.2.1

Figure Type I

This is the glint mask that is applied to the false target. In order to better visualise this stage which corresponds to the input of the project a three dimensional type of graph is selected because the distortion of the original points can be better seen in this configuration. ∙ Relevance: The glint effect in 3D represented as a deviation in distance from the middle true axis in all slant, cross and height ranges is in accordance with the angular glint theory. The actual superstructure is depicted in the middle of the graph as a continuous straight line. The distortion is depicted on the left and right of this line with circle symbols. ∙ Significance: The choice of three-dimensional representation is a meaningful way to show the difference between the original unaffected superstructure cross range coordinates and the final change by glint because it depicts the increase in target spanning as expected by the relevant laws of physics. ∙ Selectivity: The graph contains the complete ship superstructure and enables the formation of a thorough opinion about the particular step.

5.3.2.2

Figure Type II

This is the glint results as it is received by the threat signal. In order to better visualise this stage which corresponds to the output of the project a two dimensional type of graph is selected, because the wavenumber distortion can be better seen in this configuration. ∙ Relevance: The threat perceives the glint error as a wavefront distortion and this effect is depicted here. The glint effect in 2D is represented as a deviation in distance from the middle true axis marked as 0. Points that lie beyond 1 and -1 mean that the radar sensor is pointing outside the real dimensions of the naval target.

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∙ Significance: The choice of two-dimensional representation with the x-axis as the phase which corresponds to distance and the y-axis as the angular error indication which corresponds to the target cross range expansion is a meaningful way to show the distortion of the target in the y-coordinate as it is perceived by the threat radar. ∙ Selectivity: This type of figure shows the top-view distortion in the slant range axis in an intuitive manner. This distortion is true in real applications and this is the error that radar systems try to correct for example by range migration algorithms. Therefore the simulator provides a correct visualization of the numerical analysis and increased discrimination of the results.

5.3.2.3

Figure Type III

This is a graph that can be created because the target performs a pure roll motion which in high resolution imaging results in a side-view of the target. The threat system can perform such tests after storing the history of the received signal in order to ascertain its validity either as a side-view or as a top view image. According to this data mining process the threat system could output a decision of how the target is oriented. In this case the verdict would be that the target is mostly performing a roll and is a naval target of great proportions.

∙ Relevance: The target was selected to have only roll motion because this results in a side-view high resolution image and this is depicted in this figure type. The produced velocity vectors of the glinted coordinates match the input data when the glint levels are normal. Also velocity measurements are correct because they are never negative, otherwise it would be a verification and validation error. ∙ Significance: The choice of two-dimensional representation with the x-axis as the resolution cell identification number which corresponds to distance and the y-axis as the measured velocity which corresponds to the target height expansion is a meaningful way to show the distortion of the target in the z-coordinate as it is perceived by the threat radar.

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Part II - Chapter 5 ∙ Selectivity: This type of figure results after the threat has compensated for the glint effect in the slant range axis by remigrating all the slant range bins in an orderly manner, like using a range migration algorithm. Then the threat will integrate the returns with respect to time in order to perform the added value function of visualizing the collected data.

5.3.2.4

Maximum Glint Criterion

Maximum glint is obtained when the interfering scatterer has a value of 0.9 or more for reflectivity amplitude and 180 degrees phase, as shown in Figure 5.14 for Type I, Figure 5.15 for Type II and Figure 5.16 for Type III. Seeing this result at a far distance from the target a skilled radar operator may become suspicious of the large amount of angular glint. We have included this result for project validation purposes.

Figure 5.8: Long Distance High Altitude Angular Glint Effects Mask Injection

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Figure 5.9: Zero Distance Low Altitude Angular Glint Effects Mask Injection

Figure 5.10: Long Distance High Altitude Wavefront Distortion Effects at the Threat

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Figure 5.11: Zero Distance Low Altitude Wavefront Distortion Effects at the Threat

Figure 5.12: Long Distance High Altitude 3D Motion Degree Measurement

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Figure 5.13: Zero Distance Low Altitude 3D Motion Degree Measurement

Figure 5.14: Long Distance High Altitude Extreme Angular Glint Effects Mask Injection

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Figure 5.15: Long Distance High Altitude Extreme Wavefront Distortion Effects at the Threat

Figure 5.16: Long Distance High Altitude 3D Motion Degree Measurement shows strange target properties

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5.4

99

Chapter Conclusions

The conclusions from the discussion of this chapter are: This chapter focused on the challenging problem of coherent countermeasures which are meant to oppose high range resolution radar systems. For this reason a conceptual model was proposed in order to address the issue and investigate the influence of glint effects on an extended target. Verification and validation phases used a credibility metric based on pictorial vector representations of the simulator generated data. This way it was asserted that the model behaves according to the laws of physics that govern the glint effect and can provide value-added information about scenario permutations based on selected distances and heights from threat to target. Finally it was argued that by using the great possibilities of a simulator in the greater context of a software defined radar system then tactical and even strategic advantages over the adversary could be obtained by a using the resulting Simulator-defined Countermeasure System.

(47)

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Critical Thinking

http://en.wikipedia.org/wiki/Software_quality_assurance SQA http://www2.computer.org/portal/web/swebok/html/ch11#Ref2.

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Tactics is knowing what to do when there is something to do; Strategy is knowing what to do when there’s nothing to do!

- Savielly Tartakower, Chess Grandmaster, c. 1950 AD

6

Simulator-defined Countermeasure System Concept

Modern air defence at sea doctrines call for new shipborne surveillance and tracking abilities that are based on software implementations, like software-defined radar systems. This chapter contributes to investigations in the context of the ever-demanding need to forge the other side of the same coin which is countermeasures procurement for electronic protection from high range resolution sensors based again on softwaredefined radar concepts and principles.

6.1

Introduction

The verisimility domain engineering, use-case and simulator system aspects for an ISAR image of a false extended naval target are investigated. The methodology consists of hardware-to-software processes which provide information into the system, like the distance from decoy to adversary signal and the angle of arrival and softwareto-hardware processes, like the pace engine which provides for the time procession of the false target and the glint effects generator. The methodology is supported by a module interconnection language based on packet memory for rapid prototyping. The results are provided by an Interferometric Inverse Synthetic Aperture Radar simulator.

Here the ability of this simulator is ascertained to be able to provide a proof of concept towards the creation of a software defined countermeasure system (SdCS) based

University of the Aegean

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SdCS Phd Thesis 2009

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on a controlled experiment which provides side-view images for the false target. The false target generation results are presented for an approaching missile scenario and its break away aircraft. The significance of the findings is that in this manner the production methodology of the false target is enhanced with many verisimility features properly suited to the prevalent situational awareness conditions.

Decisive deterrence is one of the three political-strategic cornerstones that formulate a set of guiding principles for future Theatre Air Defence (TAD) systems development for the United States Navy, as stated by (40)[Foard, 2000, pp.387]. It is the capability to deter potential adversaries at a considerable level of power. Also this cornerstone is aimed at devising a tight defence system (theatre-wide shield) (40)[Foard, 2000, pp.

391]) that enables safe conduct of theatre-wide military operations. This capability provides counter-information warfare and information security services. The design must be based on flexible and adaptable architectures with a high degree of network availability (40)[Foard, 2000, pp. 392]. There is a need for realistic simulation programs that will ensure the reliability of the counter-information when presented to the adversary forces in real-time situations. Our contribution is the task of presenting plausible false targets that have a high probability of being mistaken as true contacts by taking under consideration the predominant laws of physics and the limitations of current technology. This task is achieved by taking under consideration the existing situational awareness condition and adapting the countermeasures output to the applicable scenario.

Nowadays in 2009 aggressor platforms are equipped with miniaturized high resolution microwave (coherent radar) sensors that are capable of resolving a ship target in slant, cross and even height ranges. A naval platform is directly confronted with these formidable and lethal threats in the modern battlespace. Especially in the condensed littoral and archipelagos areas of the Aegean Sea a ship can be overwhelmed with saturation or barrage types of aerial attacks with highly catastrophic consequences (60)[Defence Diplomacy, 2009]. Therefore the derivation of direct coherent countermeasures that hide the friendly naval assets from their opposing airborne counterparts by using obscurity and distraction principles are of paramount importance to air defence at sea operations. The main point is to be able to persuade the adversary radar operator that the false target is indeed a true contact.

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First we present an ISAR simulator that is constructed as a complex system (77)[Kostis et al, 2005] (78)[Kostis et al, 2006] (80)[Kostis, 2008]. The input in this instance is simulated data representing the hijacked replica of a threat signal multiplied by the rest of the false target slant range components. The transfer function is composed of a distance calculator that provides line-of-sight (LOS) range measurements, an interferometer module that provides angle-of-arrival (AOA) angle measurements, a pace engine that provides roll, pitch, yaw and translations functions and the digital signal processing block that provides the standard time-frequency domains transformations usual to ISAR imaging. According to LOS and AOA the output of the simulator is a side view (135)[Rihaczek, 1996, 5.1.2.3 Roll Images, pp. 441-444 5.1.2.4 Pitch Images, pp. 444-446] of the target or a top view of the target (135)[Rihaczek, 1996, 5.1.2.2 Yaw images, pp. 437-440]. Since a dominant characteristic of extended naval targets is the angular glint phenomenon as stated by (149)[Siouris, 2003, Section 3.4.2 Missile Noise Inputs, pp. 113-115], the overall design is easily extensible to provide such value added functions in the input stage (81)[Kostis, 2008] (82)[Kostis et al, 2008] (83)[Kostis, 2008]. According to the value of the interfering scatterer the dominant point scatterer in a resolution cell is displaced in the three dimensional worldspace by an amount that corresponds to a glint distance error.

This work concludes with ISAR results that correspond to two poignant threat assessment scenarios. First a stand-off high altitude long distance reconnaissance and tracking is shown. Then an approaching missile low altitude diminishing distance case is presented. The purpose of producing these results is the effort to make the false target more realistic to the adversary radar-operator (machine-human) system.

The focus is in coherent jamming where the intention is to present many false yet plausible targets to the threat signal so the adversary radar-operator loop cannot differentiate between the friendly assets and ruse of war. For the naval scenario the friendly asset is an extended target which means that there are several points on the ship’s superstructure that backscatter the threat’s signal which in turn is received and processed by an Inverse Synthetic Aperture Radar (ISAR) system. It is only necessary to synthesize a false target that has almost the same radar cross section, or electromagnetic signature, to the protected friendly asset (11)[Baldwinson, 2007]. Therefore the false target must seem to be a collection of points dispersed in slant, cross and height ranges situated in a three-dimensional worldspace (118)[Neri, 2007]. And to ensure correct

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geometrical properties and realistic false target velocities the range, velocity and heading of the threat signal must be taken into account (146)[Schleher, 1999]. The false target entity properties must always be adjusted to the threat entity characteristics.

The main line of thought is that the discovery of the decision problem lies in the just-intime status of the situational awareness. The events and developments that are engulfed in the corresponding situational awareness condition dictate the problem analysis and the subsequent development and assessment of options. For example if the threat has just started tracking the target then the immediate realization of a false target may indicate a deception attempt. In this case the output must adjust to the usual steps that are shown on the adversary’s radar screen when a target is initially tracked. The final decision about the implementation of the deception lies in the tactics plan in order. For example according to LOS and AOA the generated output is a side view image or a top view image.

We move on to the system description depicts the relationship between the inputs, transfer functions and outputs of the software system that resulted from the requirements draft process. In this case the corresponding preliminary requirements draft is depicted in Figure 6.1.

6.2

SdCS System Design

We draw upon the conclusions by (34)[Doerry, 2008] in order to adjust our simulator design to recent findings about ship motion implications for ISAR imaging. The stated conclusions are as follows: ∙ The relative motion between the naval target and the ISAR instrument is generally not known and thus presents a fundamental problem. Therefore our design must not present an altogether perfect target in the beginning of the stratagem. ∙ A planar angular perspective change of the naval target with constant angular velocity allows limited time focused images. Our design will later on provide a smooth pitching motion in order to generate side view images of the target.

Simulator-defined Countermeasure System Concept

Figure 6.1: Requirements Draft for the SdCS Project

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∙ A challenge for ISAR is achieving better estimates of the relative motion. Our design could increase the quality of the image by switching the output to several motions of variable focusing degrees. ∙ Multiple phase centers in the ISAR instrument might facilitate better estimates of the relative motion. The countermeasure design to oppose this argument may be instrument specific.

Keeping the above in mind, we proceed to create a software depiction of the proposed simulator, which is shown in Figure 6.2.

In this case the corresponding system explanation is depicted in Figure 6.3.

Software Modules Inteconnection is depicted in Figure 6.4

6.2.1

Distance Measurements

The distance calculator module contributes to the estimation of the Line of Sight (LOS) vector parameters determination, as shown in Figure 6.5.

6.2.2

Radio Frequency Interferometer

The radio frequency interferometer module contributes to the determination of the Angle of Arrival (AOA) of the threat. The most usual configuration is for the antennas of the device to be located as far as possible from each other in order to conduct conventional jamming functions, like the cross-eye method. Moreover diverse sensor position configurations are readily setup and tested for performance. In this case it is assumed that the interferometer has determined that there are two threats at a forty-five degree aspect angle to the protected naval asset, as shown in Figure 6.6.

Once the above parameters are locked then the pace engine module is injecting motion effects in the false target image. The collection of points that compose the false target are moved into space with realistic parameters. For example the sea state is observer and the false target is programmed to behave accordingly to the existing conditions.

Simulator-defined Countermeasure System Concept

Figure 6.2: Software Modules Interconnection

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Figure 6.3: SdCS Description

Simulator-defined Countermeasure System Concept

Figure 6.4: Software Modules Inteconnection

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Figure 6.5: Distance proposed calculation

Figure 6.6: Interferometer proposed configuration

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The mathematical praxis is conducted by the utilisation of affine transformation for roll, pitch, yaw and translations functions. For the purpose of extracting results that validate the output of the simulator the following statements must be considered :

∙ the heading vector of the radar is towards the x-axis of the false target ∙ the false target is pitching ∙ the Doppler resolution is the z-axis

6.2.3

Movement of the False Target

This setup produces a side-view of a real target; therefore the output of the simulator should be a side-view slant range profile and consequent ISAR image, as shown in Figure 6.7.

Figure 6.7: Movement of the false target

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Glints Effects Injection

Angular glint is representative of extended naval targets. The inclusion of this effect increases the credibility factor of the decoy playback signal at the adversary radaroperator station. In order to uphold the credibility quality of the experiment the interfering scatterer positions are placed at ninety degrees with respect to the aspect angle setup, as shown in Figure 6.8.

Figure 6.8: Prominent and interfering point scatterers

6.2.5

Digital Signal Processing Use-Case

The use-case resulting from the requirements study is shown in Figure 6.9.

The use case was desinged aacording to (52)[Gottesdiener, 2002].

(90)[Kulak, 2003]

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Figure 6.9: Use Case

6.3

Proof of Concept with a Controlled Experiment

A proof of concept study is a trial to demonstrate that a fact or concept or stratagem is possible or valuable using a small number of strictly selected entities and methods. It is a short realization or synopsis of a certain method or idea that is conducted in order to demonstrate the degree of feasibility or a demonstration in principle. Furthermore its purpose is to verify that some concept or theory is probably capable of exploitation in a useful manner. In this paper the effort is to conduct a proof of concept study for the information system that would be capable to sustain a stand-off expendable and autonomous decoy system for air defence at sea purposes. Such electronic decoy is a device meant as a distraction in order to draw attention to it and thus conceal an important and usually very valuable friendly asset from an adversary party. The particular proof of concept study is conducted by using verification and validation analysis routes.

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False Target Generation Results

The evaluation of the simulator output for a characteristic threat assessment scenario is shown in Table 6.1.

A B C D E F G H

Threat Type

Range [Knmi]

Missile t=0 Missile t=1 Missile t=2 Missile t=3 Aircraft t=0 Aircraft t=1 Aircraft t=2 Aircraft t=3

38 19 5 1 38 42 46 50

Processes Aspect Height Angle [m] [degrees] 45 10000 44.5 100 45 40 44.5 20 45 10000 44.5 10000 45 10000 44.5 10000

Glint at target A1 B1 C1 D1 E1 F1 G1 H1

Glint at threat A2 B2 C2 D2 E2 F2 G2 H2

SRP

ISAR

A3 B3 C3 D3 E3 F3 G3 H3

A4 B4 C4 D4 E4 F4 G4 H4

Table 6.1: Threat Assessment Scenario

The visual depiction of this scenario is shown in Figure 6.10.

The fire control wavelength permutations of an X-Band Fire Control (XFC) at a wavelength of 0.03 to 0.04 m, as shown in (106)(Lynch, 2004) are now investigated. An advantage of the simulator is the easy and adaptable change of the operational parameters. For example the adaptation can easily change to a J band naval radar of 10 to 20 Ghz should that was the threat tracking the electronic countermeasure. In order to increase the verisimility of the results multiple layers that correspond to reflectivity coming from lower height coordinates are added to the final image. In this case one additional layer is presented. This layer is not injected with glint effects in order to demonstrate the presence and absence of the glint generator module.

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Figure 6.10: Threat Scenario

6.4.1

Approaching Missile Scenario

The scenario starts by considering that the missile sensor acquired target at 45 degrees aspect angle with half a degree change in order to achieve the required cross range resolution. From the set of Figures A, B, C and D it is deduced that the output is slightly fluctuating with respect to the distance.

6.4.2

Stand-Off Aircraft Surveillance and Tracking Scenario

The scenario continues by considering that the aircraft sensor is moving away from the threat. From the set of Figures E, F, G and H it is deduced that the output again is slightly fluctuating with respect to the distance.

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Figure 6.11: A1 - Glint at the target - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.12: A2 - Glint at the radar - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.13: A3 - Slant Range Profile - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.14: A4 - ISAR Image - Missile at 70.420Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.15: B1 - Glint at the target - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.16: B2 - Glint at the radar - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.17: B3 - Slant Range Profile - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.18: B4 - ISAR Image - Missile at 35.210Km, 100m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.19: C1 - Glint at the target - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.20: C2 - Glint at the radar - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength

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Figure 6.21: C3 - Slant Range Profile - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength

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Figure 6.22: C4 - ISAR Image - Missile at 9.265Km, 40m, 45 aspect angle, 0.03m wavelength

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Figure 6.23: D1 - Glint at the target - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.24: D2 - Glint at the radar - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.25: D3 - Slant Range Profile - Missile at 1853m, 20m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.26: D4 - ISAR Image - Missile 1853m, 20m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.27: E1 - Glint at the target - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.28: E2 - Glint at the radar - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.29: E3 - Slant Range Profile - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.30: E4 - ISAR Image - Aircraft at 70.420Km, 10000m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.31: F1 - Glint at the target - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.32: F2 - Glint at the radar - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.33: F3 - Slant Range Profile - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.34: F4 - ISAR Image - Aircraft at 77.833Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.35: G1 - Glint at the target - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.36: G2 - Glint at the radar - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.37: G3 - Slant Range Profile - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.38: G4 - ISAR Image - Aircraft at 85.246Km, 10000m, 44.5 aspect angle, 0.03m wavelength

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Figure 6.39: H1 - Glint at the target - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.40: H2 - Glint at the radar - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength

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Figure 6.41: H3 - Slant Range Profile - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength

Simulator-defined Countermeasure System Concept

Figure 6.42: H4 - ISAR Image - Aircraft at 96.660Km, 10000m, 45 aspect angle, 0.03m wavelength

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Discussion

There are two main approaches in the construction of countermeasures in general. The first approach tries to provide an output that is particular in jamming or neutralizing an existing system. The other approach tries to generate an output that is close to the laws of physics so any device is bound to pick up the false signal as recognized and valid.

This effort is closer to the latter approach.

From this work the following key points from this paper are summarized as follows:

∙ The simulator can easily create the appropriate permutations of diverse range, height, aspect angle and wavelength for the generation of the false target. The purpose of producing these results is the effort to make the false target more realistic to the adversary radar-operator (machine-human) system. ∙ The simulator can be seamlessly integrated to the context of a software-defined countermeasure system (SdCS). In this manner the simulator can support a decision making system that will produce the correct output according to an assessment made on the basis of the characteristics of the threat signal. ∙ Countermeasure data can be created just-in-time thus eliminating the need for huge memory banks of playback false target data. By using miniaturised equipment, like FPGA’s, the simulator can be mounted into remote decoy systems.

These decoy systems can be mounted in a platform that can simultaneously support submersible, seafaring and aerial functions. In this manner the softwaredefined countermeasure system can be augmented into providing better coverage and functionality. Also its survivability factor is highly increased. ∙ The SdCS can be hosted on remote stand-off decoy platforms and act as frontline of defence electronic warfare systems. In this manner the value of the standoff decoy is very low compared to the high value of a stand-off SdCS mounted on a maritime patrol aircraft and its forward position is justified. Moreover such forwarded autonomous SdCS systems should protect their code and data elements by using an encryption system.

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∙ The simulator can generate outputs that are valid or even non-valid. All these outputs are useful in the deception of the adversary. An on-board simulator may create non-plausible false targets thus driving the adversary operator to question the validity of the encounter at this area and directing its forces elsewhere. A stand-off SdCS may create high validity targets in order to become a honeypot and lure the adversary radar operators to direct their efforts in that area. The ultimate goal is the deception of the opposite human element.

6.6

Chapter Conclusions

The conclusions from the discussion of this chapter are: A contribution to investigations in the context of using a simulator in the context of a software-defined countermeasure system is presented in this paper. It was stated that the simulator can be used to create the just-in-time output needed according to a decision making system that takes into account the position and heading of the threat signal. A proposed simulator design for this purpose was presented and results regarding a characteristic fire control radar threat assessment scenario were provided. Sensor miniaturisation and parallel processing currently render possible the realisation of a flexible, economic and practical SdCS decoy platform. The final argument is raised on the usage of this software tool for actual obfuscation and deception actions for air defence at sea applications by stating that all output is useful. Tactical and even strategic advantages can be gained over the adversary by adjusting the simulator output to high or low reality levels.

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Part III Domain Reusability Analysis: Extended Information Warfare Applications

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The desire to surprise the enemy by our plans and dispositions, especially those concerning the distribution of forces, is at the root of all operations without exception.

- Carl von Clausewitz, Vom Kriege, c. 1832 AD

7

Domain Reusability for Computer Networks Warfare

Electronic Warfare and Computer Network Warfare operations are conducted into different action theatres and employ assorted laws of physics, technological assets, communications mediums and even political doctrines. Simulator-defined countermeasure systems concepts and techniques allow the generation of false naval targets for the purpose of security by obscurity in the field of electronic warfare. This chapter proposes that the experience and expertise of creating simulator-defined false naval targets is very beneficial to the field of security by obscurity for computer network warfare.

7.1

Introduction

During the eighties there was a big chance a floppy disk that was inserted into a personal computer running MS-DOS 6.22(TM) or Windows 3.11(TM) to be infected with the Brain, the Stoned or the Italian virus. Without internet connectivity the only port of entry was the floppy disk reader device. This fact classified the personal computer as a point target for a virus introduction to the system. At the same time radar scopes could see a target as a point scatterer on their plan position indicator scope screens. A characteristic example of a Plan Position Indicator (PPI) is depicted in Stanley Kubrick’s 1964 movie classic "Dr. Strangelove: Or how I stopped worrying and Love the Bomb".

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These two examples from two distinct fields of electronic warfare and computer networks warfare form the parallelism shown in Figure 7.1.

Figure 7.1: An 80s personal computer behaved like a point scatterer in terms of connectivity like the inverse scattering depiction on a plan position indicator (PPI) radar screen.

In the 2000s personal computers were interconnected via the internet revolution availability to the public. The force of the transmission control protocol and user datagram protocol enabled 65535 communications ports. Especially higher valued ports (over 1024) became the target of ingenious and diverse malware and virus software attacks. Thus the modern pc had become an extended target like a naval superstructure where many points contribute to the acquisition of the target’s valuable information as compared to one of the most common ISAR images of USS Crockett, found at http://radar-www.nrl.navy and accessed on 11th August, 2009. This new analogy between the fields of electronic warfare and computer networks warfare is shown in Figure 7.2.

In previous work it was shown that a modelling and analysis method was developed in order to represent an electromagnetic spectrum electronic warfare application con-

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Figure 7.2: A modern personal computer is an extended target like its naval equivalent.

cerning the creation of false naval extended targets for air defence at sea purposes (80)(Kostis, 2008). This modelling and design approach resulted in the concept of the simulator-defined countermeasure system (85)(Kostis, 2009).

And having just established the extended target analogy the outcome is that at least the targets in both cases share the same notion. Now the problem that emerges is how economical it would be to reuse the experience and expertise gained from the electronic warfare naval extended target case to the field of computer network security issues with the personal computer as an extended target. Could an electronic warfare specialist be employed as a computer networks security officer and vice versa with ease?

In this paper the proof comes as the degree of domain reusability of the established methodology for the electromagnetic spectrum case as investigated in order to represent the domain of computer networks warfare dual. The analysis begins with a component-based reusability for reuse (173)[Wang, 2002]. Analytically the depth factor for the conceptual modelling of a false registration authority as compared to the false naval target is presented. The complete domain reusability is further established

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by looking into the maintenance of an existing registration authority. The research effort is targeted towards the level of parallelism between the two cases both in conceptual modelling and in code maintenance terms (20)(Braga, 1996), as shown in Figure 7.3.

Figure 7.3: Domain reusability depth factor estimation.

The flow of research is justified because the field of electronic warfare is more mature than its computer networks warfare counterpart. The focus is on bridging the knowledge gap between the two disciplines by accenting the obscured parallel concepts between the two disciplines which encompass terminology, doctrine and model-driven design fields and concepts. This is not an isolated effort as shown by (153)(Smith et al, 2005).

7.2

Computer Networks Warfare

The conceptual modelling electronic warfare methodology can be applied to the creation of false Registration Authorities. Moreover Public Key Infrastructure database

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maintenance actions can be conducted by using modularity and increased complexity techniques acquired again from the electronic warfare simulator duality. Many similar if even identical entities, processes, implementation procedures and maintenance techniques are detected and clearly identified leading to the conclusion that research in one discipline is very beneficial to the other in terms of design time overhead, maintenance time turnover and return on investment.

7.3

Elements of Domain Reusability

Up to now we have devised a computing methodology in order to create false radar target entities. Also an effort is made so that these entities possess qualities that resemble the real situation as close as possible. By looking at the steps of the application domain definition and problem space decomposition for the electronic warfare case we found that the same computing methodology can be used for the computer networks warfare case. Generally the community of interest (COI) for this project is military training and network-centric operations and warfare (11)[Balci et al, 2007, p.176]. For example the application domain definition for the computer networks case is shown in Figure 7.4, which is identical in principle to the previous study for the electronic warfare case.

7.4

Domain Reusability Depth Factor

Domain Reuse is the ability to use the database that supports an existing project again outside the task or application system that created and used its facilities (115)(Muller, 1999, p. 144). Domain Analysis is a necessary step in order to begin the process of systematic software reuse (145)(Sametinger, 1999, p. 58) which is shown in Figure 7.5.

The depth factor will be assessed by examining the conceptual modelling of a false registration authority and the modular code programming in order to maintain databases that support Public Key Infrastructure Systems (76)(Komar, 2003).

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Figure 7.4: Computer Networks Warfare domain reusability

7.4.1

Conceptual Modelling for False Registration Authorities

The conceptual model is the initial step in the production of an abstract yet functional representation for a particular situation. The composition of a conceptual model is made of the Application Domain Definition, problem Space Decomposition, Entity Abstraction Degree and Entity Relationship Identification (119)[Neugebauer, 2007].

7.4.1.1

Application Domain Definition

The Application Domain Definition defines the theoretical and practical milestones that have to be achieved during the complete process. In this case the creation of a false registration authority (RA) can hide a real RA thus providing security by obscurity. Or it can provide a honeynet of a false PKI in order to lure attackers and capture their methods and intentions (54)(Grimes, 2005).

And for the networks case: that the countermeasure system shall: ∙ accept as input an extended computer target (ports 0 to 65535) at t = 0.

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Figure 7.5: Domain analysis between EW and CNW cases.

∙ utilize the transfer function I that provides a database of behaviour actions (Registration Authority) from t = 0 to t = τ (duration of operation). ∙ utilize the transfer function II that provides the necessary transformations and preparations of the behaviour actions (tcp/udp format and similar low level considerations) for transmission to the propagating medium( the internet). ∙ provide as output a database of properly prepared data for computer network systems security by obscurity countermeasure functions.

7.4.1.2

Problem Space Decomposition

The entities and processes that must be represented for the successful accomplishment of the simulation are hereby defined. For this particular project the entities involved

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are shown in Table 7.1 and the processes are shown in Table 7.2.

Entities 1

2

3

4

5

6 7

8

Simulation Reality Registration Authority Simula- Server hardware and software tion, Open ports emulation characteristics and functionalities Computer entity emulation, Op- Network map erating System simulated visible attributes Simulated network routes from Network gateway real gateway to false Registration Authority Simulated success on Network Network Probing, Network Probing, Network Mapping, Mapping, Information gathering Information gathering , Open for possible vulnerabilities of ports, OS Version, Service Packs the found network device Reality factors addition that pos- Black hat professional’s actual itively affect the black hat pro- analysis of the information gathfessional’s opinion about the va- ering results and decision maklidity of the attack on the target ing about the validity of a netnetwork work probe Flow of false data through time Actual packet and traffic inspection Registration Authority decoy Black hat professional has inserver simulates responses of a creased confidence of being in compromised network device control.

Full simulation of a compro- Black hat professional’s actions mised Registration Authority (data gathering, denial of service server and network. attack, root kit installation) Table 7.1: Computer Networks Warfare Entities

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Now we can draw the necessary associations between the entities and come up with the corresponding processes, as shown in Table 7.2. Again as above the comparison between the reality and the simulation is strongly taken into account.

A B

C D

E

F

G

H

Processes Simulation Reality False network topology Actual network topology Ping times generated by the false Ping times from black hat to topology white hat computer - main point of network topology Allows the black hat profes- Successful entry attempt sional to a route to the false RA Details a false network environ- Information gathering about the ment as it would be after a suc- real network cessful illicit entry attempt Feed the pace engine with Actual network traffic verisimility attributes imitating true traffic Simulated different data traffic Common actual maintenance with respect to time increases the (service packs, admin observaverisimility of the (6 - Flow of tions, service requirements, new false data through time) terminals addition What the black hat professional Information gathering concluded sees - he false Registration Au- for the specific target - possibilthority ity of pirated information storage Reveals false certificate data Black hat professional is in confrom simulated controlled secure trol, starts main actions and reareas veals real motives - - possibility of pirated information storage Table 7.2: Computer Networks Warfare Processes

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Entity Abstraction Degree

The level of abstraction of the project is defined in this stage, like the level of accuracy, precision, resolution and fidelity of the involved entities and processes. Since this is a preliminary investigation on the depth factor estimation this step is not covered in this work. More information about this step can be found in (84)(Kostis, 2009).

7.4.1.4

Entity Relationship Identification

We want to prove in this paper that our existing Entity Relationship Identification can be applied in the network case. The entity relationship identification structure has remained the same, as shown in Figure 7.6.

A careful inspection and comparison of Table 7.1 and Table 7.2 with Figure 7.6 shows that the entities and processes as states correspond to the electronic warfare existing version of the Entity Relationship Identification layout. This figure depicted the electronic warfare case for the false naval target generator.

Therefore the first intermediate conclusion is that conceptual modelling for the electromagnetic case is indeed beneficial when applied to a computer networks warfare case.

7.4.2

Implementation Techniques for PKI Databases

Implementation techniques include code creation and code maintenance. Two techniques that were effectively used in the construction of the electronic warfare case were the concepts of modularity and increased complexity. Here these concepts are put into the frame of the computer networks case in order to estimate the profit from any similarities.

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Figure 7.6: E-R Identification is the same for the electronic warfare and the computer network warfare cases.

7.4.2.1

Modularity

The concept of modularity is universal in the coding of complex systems. The security professional should be very familiar with the ability to code in a well defined boundary method which allows for easy interfacing. Here an example is drawn from the maintenance of the Public Key Infrastructure database that serves the University of the Aegean.

During 2003 there was an update of the database to a new server that runs SQL Server 2005. Unfortunately there was an incompatibility with the old procedure of SQL Server 2000 and the database was rendered useless. After careful inspection it was found that if there was a way to insert a module and not a database procedure the result would be an again functional database. In other words a way was needed to simulate the effects of the stored procedure without having to recode the entire database struc-

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ture with the new Microsoft∙ instructions. The implementation process in this modular manner is shown in Figure 7.7.

Figure 7.7: Modularity in PKI Databases.

7.4.2.2

Increased Complexity

The increased complexity concept is particular. The scripting of the modules are specific to each case. Nevertheless adopting the increased complexity approach is very beneficial because it shows the steps that should be taken in order to help test the stages of the coding (68)(Jarzabek, 2007). First only the personal certificate case was considered. The attributes of the certificate were hard coded and the coding was tested only against one certificate case.

When these attempts were successful the attributes of the certificates were opened to input data from a user. When this test was successful then the rest of the certificate types, namely server, domain controller and smart card were implemented in the same methodology. The complete process is shown in Figure 7.8.

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Figure 7.8: Increased complexity in maintaining a Public Key Infrastructure Database system.

The code scripting and maintenance techniques documented above were taken from the electronic warfare case. Because modularity was used to create all data manipulation before the database storage, so in effect no stored procedures were used as was in the electronic warfare case. Increased complexity in the electronic warfare case came from increasing the target precision and fidelity. In the computer networks warfare case the different kinds of certificates were treated as ever increasing in diversity.

Therefore the second intermediate conclusion is that the same software architecture was passed on from the electronic warfare to the computer networks warfare fields.

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Discussion

The conduct of a complete cost assessment of the domain reuse applicability between the electronic warfare and the computer warfare fields must be based on elements of a strategic cost system (98)(Lianabel, 2004). The most important tactical elements of such a system is its ability to provide accuracy estimation and decision making information used to allow or halt further development.

Judging from the conceptual modelling development for false registration authority which was based on the radar systems equivalent the result is a high degree of accuracy between the two attempts. A successful attempt to match the entities and the processes between the two fields yielded encouraging results. Therefore the cost of developing a conceptual model for the creation of false registration authorities is low since an existing domain model was consulted.

And judging from the modularity and increased complexity development part there was accurate reuse of experience gained by the software architecture and implementation modelling concepts taken from the electronic warfare field.

The cost function evaluation relates to a satisfactory high domain reusability depth factor which means lower development costs for conceptual modeling, algorithm design and simulator coding. It is evident that final product realization times could be reduced by this domain reuse effort.

The secret behind the successful reusability process is the component-based development for reuse which was meticulously followed for the electronic warfare case.

7.6

Conclusions

Electronic warfare simulator-defined radar countermeasure concepts and techniques of false naval target generators have very high applicability to the conceptual modelling and code maintenance fields for computer networks warfare. A preliminary investigation in the field of Public Key Infrastructure proved the deep depth factor reusability of the electronic warfare to the computer networks warfare fields. This research showed

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shorter implementation times and provision of tested solution patterns both in preliminary design steps, like the conceptual modelling of a false registration authority, and in actual code maintenance steps, like the simulated stored procedure solution for the University of the Aegean Public Key Infrastructure database corrective case. Surely an Information Technology Specialist can enhance skill and perception from looking into ways to reuse elements from electronic warfare to computer networks warfare fields which are righteously classified under the general scope of Information Warfare.

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Conclusions Conclusions: Deception by Obscurity for Information Warfare Applications

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The most dangerous moment comes with victory.

- Napoleon Bonaparte, Emperor of the French, c. 1800 AD

8 Conclusions

The needs of the real world are satisfied with the invention of a suitable methodology.

And the demands of the academic community are met with the devise of a relevant proof of concept. Potential for further advancement is established.

8.1

The SdCS concept: A new approach to coherent countermeasures

Software-defined radar concepts and techniques can be used in an effective and adaptable manner in order to provide deception countermeasures against coherent radar systems by utilizing a simulator core. The main contribution of this work is the derivation of a computing methodology which can be applied for both electronic warfare and computer networks warfare fields. For this reason a conceptual model was proposed in order to address the issue and investigate the levels of verisimility that can be achieved.

Analytically verification and validation phases used a credibility metric based on pictorial vector representations of the simulator generated data. This way it was asserted that the model behaves according to the laws of physics that govern the glint effect and can provide value-added information about scenario permutations based on selected distances and heights from threat to target.

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The main purpose of this work is to provide security functions through obfuscation of the real asset in an environment of other false entities thus further proving deception services by luring the hostile parties to engage false entities or in any way avoid the real asset.

Finally it was argued that by using the great possibilities of a simulator in the greater context of a complete software defined radar system we can obtain tactical and even strategic advantages over the adversary. Moreover it is worthwhile to point out that the design tools of coherent countermeasures, being dynamically pictorial in nature, are no different than a painting or a movie feature. As is art forgery, the more the resemblance to the real prototype the higher the chances a buyer will be persuaded to invest in the false copy. Because the buyer will be infected, as Tolstoy so vividly explained, with the artistic persuasion of the false masterpiece. In a final note, the act of implementing coherent countermeasures using a simulator base is an integral part of the amazing field of Art.

8.2

Future Work

The potential for future work is diverse. At least four major directions can be identified.

8.2.1

Enrichment of the software code

∙ Top-view add on ∙ Middle views add on ∙ Sonar deception complement ∙ Sea clutter add-on (8)[Antipov, 1998] ∙ Multipath effects ∙ Reflection strength - less than 20dB from primary ∙ Path loss (attenuation) and other noise additions

Conclusions

8.2.2

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∙ Computer networks warfare

8.2.3

Decoy platform elaboration

∙ A study in implementing a stand-alone airborne, floating and submersible platform for the SdCS concept. ∙ Possible requirements would include an autonomous platform which should be able to get airborne, land on sea and conduct seafaring and when needed be submersible. ∙ An important issue that needs to be further investigated is the protection of the on-board code. A study should be conducted whether a PKI could protect the sensitive code or added security features should be as well added.

8.2.4

Code execution speed-up

∙ This is a general field which involves parallel programming. The simulator core is heavy on Fourier transforms.

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Cover Page Kallima inachis, perhaps the most wonderful of all imitative insects, is the leaf-butterfly of India. In his website, Mr. Sunil Kumar has posted the figure that appears on the cover, which can be found at http://sunilblog.wordpress.com/2009/ 09/01/leaf-butterfly/. This particular figure was selected because it encompasses all the main points of this PhD thesis as a duality relationship.

Evolution has enabled this butterfly to increase her verisimility levels to an amazing degree of leaf mimicry. Because the opposite was not possible, nothing in nature could or had the incentive to evolve to look like the butterfly which is blue and yellow on the inside of her wings. Kallima inachis’ instinct has led her to choose to rest on three distinctive false targets achieving perfect security by obscurity. This amazing quartet cannot be easily resolved to its components even from an almost zero distance by an optical observer. This is a characteristic example of security by obscurity from a target that can blend to its surroundings.

This PhD thesis has attempted to provide the dual principle. Since a naval target cannot be changed to blend with its surroundings a simulation world was needed that can furnish the leaves (false naval targets) around the butterfly (friendly naval asset) on demand and with a high quality factor. The microwave eyes of a high resolution radar or very low frequency ears of a high fidelity sonar will still have the equivalent hard time to distinguish the respective stratagem as the false target verisimility levels tend towards multiple valid naval vessels in electromagnetic signatures and sound levels instead of an actual one real ship. This is a characteristic example of security by obscurity from a target that can falsely multiply itself to its surroundings.

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Kallima Family of Butterflies The Kallima family of butterflies is fantastic. Please indulge to her magnificence: http://www.wku.edu/~smithch/wallace/S318.htm Kallima inachis, the dead-leaf butterfly, provided by Wallace A. R., The Protective Colours of Animals which appeared in the collection Science for All, in 1879, with Charles H. Smith’s as acting Editor. http://www.dactyl.org/directors/vna/VNStalk.htm Kallima paraletka, by Yves-Pascal Dion, 1998. http://www.flickr.com/photos/toddalperovitz/2092798784/ Kallima formosana from the Taipei Zoo. http://www.yourdictionary.com/real-world http://dictionary.die.net/realworld the practical world as opposed to the academic world http://en.wiktionary.org/wiki/real_world

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[4] Allen B., 2007, Ultrawideband Antennas and Propagation for Communications, Radar and Imaging, John Wiley & Sons [5] Allen J. H., Barnum S., Ellison R. J., McGraw G., Mead R., 2008, Software Security Engineering: A Guide for Project Managers, Addison Wesley Professional [6] Ammann P., Offutt J., 2008, Introduction to Software Testing, Cambridge University Press [7] Anderson R. J., 2005, Security Engineering: A guide to building dependable distributed systems, Wiley [8] Antipov I., 1998, Simulation of Sea Clutter Returns, DSTO-TR-0679, http: //hdl.handle.net/1947/4132 172 [9] Arslan H., 2007, Cognitive Radio, Software Defined Radio and Adaptive Wireless Systems, Springer [10] Balci O., Ormsby W. F., 2007, Conceptual Modelling for Designing LargeScale Simulations, Journal of Simulation, pp. 175-186, Operational Research Society Ltd, 1747-7778/07. 5, 6, 7, 22, 31, 41, 103, 157

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Index

Abstract in Hellenic, iv Aircraft Dornier Do-217, 20 Heinkel He-177 Greif, 20 Angular Glint, 81 Anti-Ship Guided Bomb, 20 Fritz-X, 20 Beamwidth, 71 Coherence, 45 Coherent Radar, 5 Coherent Countermeasures, 9 Computer Networks Warfare Domain Reusability, 157 Computer Virus, 153 Controlled Experiment, 5 Credibility Metric, 90 Defence at Sea Simulators Countermeasures, 22 Dr. Strangelove, 153 ENIGMA, 19 Extended Target, 81

Phased Array Antenna, 71 PKI Database Registration Authority, 163 Problem Statement brief, 4 detailed, 5 Proof of Concept Controlled Experiment, 113 Public Key Infrastructure, 156 Radar System Plan Position Indicator, 153 SCR-270, 47 Reflectance Amplitude, 59 Reflectivity Initial Phase, 59 Requirement, 38 Resolution Cell, 58 Sampling, 45 Sicinnus, 37 Signal Processing Block, 71 Simulation Engineers, 44 Snorkel, 20 Subject Matter Experts, 44 Thucydides, 29

False Registration Authority, 158 Kriegsmarine, 15 Malware, 154 Monopulse, 21 Monostatic Radar, 51 Pace Engine Computing Moving Force, 68

University of the Aegean

USS Crockett, 154 Validation, 90 Critical Thinking Process, 91 Glint Module, 90 ISAR Module, 90 Pictorial Inspection, 90 Verisimility

193

SdCS Phd Thesis 2009

194 Concept, 6 Requirements Engineering Military, 40 Virtual Worldspace Digital World, 70

Index

Simulator-defined Countermeasure System Concept

195

Equations Index TM3: Space-Time progression of input data, 43 TM4: SdCS Output, 43 CO1: Conventional Resolution, 45 ML2: Roll motion, 69 ML3: Naval target movement through time, 69 ML4: Movement Matrix, 69 ML5: Angles, 69 ML6: Pure Roll Motion, 69 ML7: Pure Pitch Motion, 69 GL1: Wavenumber, 81 GL2: Distance between the prominent and the interfering scatterers within the same resolution cell, 81 GL3: Midpoint distance between the prominent and the interfering scatterers within the same resolution cell, 81 GL4: Midpoint Vector, 82 GL5: Midpoint Unit Vector, 82 GL6: Distance between the radar and the midpoint, 82 GL7: Vector between the radar and the midpoint, 82 GL8: Unit vector between the radar and the midpoint, 82 GL9: Vector normal to the midpoint vector, 83 GLA: Distance between the prominent point and the radar sensor, 83

196

Equations Index

GLB: Line of sight vector, 83 GLC: LOS unit vector, 83 GLD: Angle between the transverse glint vector and the line of sight vector, 83 GLE: Miss distance, 84 GLF: Glint effect in 3D at the false target, 88 GLG: Glint effect at the false target, 89 GLH: Rotation Vector, 89