Military Embedded Systems July/August 2020

@military_cots

John McHale

Handling information – and heat

Technology Update

AI aims at human/machine teams

Special Report

Satellites and cyberwarfare

Mil Tech Trends

Lower the heat on military DAUs MIL-EMBEDDED.COM

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July/August 2020 | Volume 16 | Number 5

MANAGING THE MILITARY’S BIG DATA CHALLENGE P 32

P 26 Can you really simulate an FPGA device?

By Max Taylor-Smith, Entropy Electro-Mechanical Solutions

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TABLE OF CONTENTS 14

July/August 2020 Volume 16 | Number 5

36

COLUMNS Editor’s Perspective 7 Handling the information overload – and the heat

By John McHale

Technology Update 8 AI-enabled vehicles will usher in true human-machine teaming in the field

By Lisa Daigle

Mil Tech Insider 10 Leveraging secure commercial routing technology to protect data-in-motion

By Mike Southworth

FEATURES SPECIAL REPORT: Cyberwarfare Technology 14 Are satellites a cyberwarfare target?

By Sally Cole, Senior Editor

MIL TECH TRENDS: Rugged Computing & Thermal Management 18 Hot problems: Designing a thermally optimal data-acquisition unit

By Pat Quinn, Curtiss-Wright Defense Solutions 22 Bridging the cooling gap in high-speed embedded systems

By Steve Gudknecht and Jordan Sudlow, LCR Embedded Systems

THE LATEST Defense Tech Wire 12 By Emma Helfrich

26 Can you really simulate an FPGA device?

By Max Taylor-Smith, Entropy Electro-Mechanical Solutions

INDUSTRY SPOTLIGHT: Leveraging Big Data for Military Applications

Editor’s Choice Products 44 By Mil-Embedded Staff Connecting with Mil Embedded 46 By Mil-Embedded Staff

32 Managing the military’s big data challenge

By Emma Helfrich, Associate Editor 36 Addressing the data challenges of modern electronic warfare and radar

By Chris Miller, Keysight 18

32

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ON THE COVER: The data-gathering challenge facing both the users of military technology and the manufacturers of these tools: Acquiring that glut of data in contested environments and relaying it in an efficient way. Successful gathering, processing, and analyzing of this precious information will effectively change warfare as it is understood today.

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Behlman leads the pack again!

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24 Phoenix International – Phalanx II: The ultimate NAS 3 WinSystems – Embed mission success 24 Z Microsystems, Inc. – Size optimized

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MILITARY EMBEDDED SYSTEMS

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EDITOR’S PERSPECTIVE

Handling the information overload – and the heat John.McHale@opensysmedia.com

By John McHale, Editorial Director

Information overload: another way of saying big data challenge. In other words, there is way too much information out there for military operators to sift through – whether it’s sifting through signals intelligence, video feeds from unmanned aircraft, or text such as social media posts from suspected terror groups. The amount of data gathered is so massive that it’s impossible to properly search it all in a reasonable amount of time.

Even more daunting: No matter how large that pile of data might be, we still don’t have enough data gathered.

Depressing, for sure, but not hopeless. Technological solutions are being leveraged to gather that data. We see it in our everyday lives, for example when shopping online.

The other day I looked at a new golf club on a manufacturer’s website and the ad for that club followed me to Facebook, to LinkedIn, all over the place. Ever wonder how Barnes and Noble knows what you like to read? The company mines the data behind your book purchases and makes recommendations to you for your next book based on your data.

But that way of using data is kind of old hat. More urgently, big data also figures into the challenge the medical world and the government have in tracking the spread of the COVID-19 virus. That set of critical tasks may actually more closely mirror the challenge faced by military regarding big data. Both are matters of life and death – both require new information every day – both will never ever truly have enough data to fight the virus or fight the enemy without casualties.

While it is true that commercial applications and game systems have acknowledged this challenge and apply big data in creative ways, “these industries do not operate in the life-and-death environments that warfighters deal with daily,” says Dr. Scott Neal Reilly, senior vice president and principal scientist at Charles River Analytics in a feature on page 32 by associate editor Emma Helfrich. “Developing data-driven systems that can be validated to the extent necessary for deployment in real-world, military contexts is a major challenge for the community.”

One major tool the U.S. Department of Defense (DoD) is using to solve the big data problem is artificial intelligence (AI), which Helfrich also covers in her feature.

“The DoD AI strategy is prioritizing systems that reduce cognitive overload and improve decision-making,” says Michael Rudolph, aerospace and defense industry manager for MathWorks, in the feature. “In order to speed up that OODA [observe, orient, decide, act] loop, AI needs to make earlier predictions and identify emerging issues from a variety of data sources. With big data in AI, the question is not just how much data but one of data and feature quality.”

Much of the big data challenge is being undertaken by software engineers, those specializing in AI and machine learning. However, performing AI functions in software requires very powerful computers and processors, which brings us to a problem that military embedded system designers have been facing for decades – thermal management.

www.mil-embedded.com

Every year, processor performance gets faster and more impressive, but the heat they generate remains a problem military commercial off-the-shelf (COTS) suppliers must solve through such techniques as air-flow-through cooling, liquid cooling, or conduction cooling.

Solving that speed/heat problem never gets easier, especially in VPX-based systems.

“With the advent of individual 6U VPX modules that surpass 200 watts of dissipated power, traditional conduction cooling approaches for heat removal are being pushed to the limit and with that we see the emergence of the various VITA 48 module level cooling strategies,” say Steve Gudknecht and Jordan Sudlow of LCR Embedded Systems in their article on page 22. The authors go into an overview of different cooling techniques in the piece.

In our Industry Spotlight on thermal management, Max Taylor-Smith of Entropy Electro-Mechanical Solutions takes a very in-depth approach on how to simulate the thermal challenges inherent with FPGAs. While these devices enable unprecedented performance for signal processing applications, they are also notorious for turning up the heat as they blaze through reams of data.

In his piece, Taylor-Smith observes that the approach to thermal solutions for higher-power FPGA versions has remained relatively stagnant for the last 10 years. Read his take on this situation on page 26.

Another not-to-miss article on beating the heat: Pat Quinn of Curtiss-Wright Defense Solutions illustrates the ways in which designers can manage thermal issues that arise in data-acquisition units for extreme environments, like those used for flight test instrumentation.

Read this one on page 18.

MILITARY EMBEDDED SYSTEMS

July/August 2020 7

TECHNOLOGY UPDATE

AI-enabled vehicles will usher in true human-machine teaming in the field

By Lisa Daigle Autonomous vehicles in science fiction and lore – think Asimov’s “Sally” self-driving car, Arthur C. Clarke’s automatic cars, or Knight Rider’s KITT automobile with an attitude – are often able to operate independently and in concert with their humans.

The phrase “no longer science fiction, but science fact” gets thrown around so much that it’s lost some of its punch, but in the case of the Army Research Lab’s work on artificial intelligence (AI)-enabled vehicles, it’s an apt observation.

Human-machine teaming – in which soldiers trust their vehicle systems to operate alongside them as actual partners instead of at peoples’ specific direction – is well on its way to being real, as the U.S. Army is working on several projects related to artificial intelligence (AI) and machine learning (ML).

Field and combat vehicles need autonomy not just for linear mobility but more realistically to navigate and act on many fast-changing variables needed to maneuver in complex terrain, against incoming hostile attack, or counter to threats on land, at sea, or from the air. These vehicles also must operate at what’s known as “operational tempo,” or a normal operating speed compared to what is going on around them.

The U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) designated several research programs as essential for future soldier capabilities. One such initiative, the Artificial Intelligence for Maneuver and Mobility (AIMM) Essential Research Program, is working toward reducing soldier distractions in the field through the true integration of autonomous systems in Army vehicles.

Dr. John Fossaceca, AIMM program manager, says that his team is trying to develop the foundational capabilities that will enable autonomy in the next generation of combat vehicles.

In a recent episode of the ARL’s “What We Learned Today” podcast, Fossaceca details the kinds of tasks the next-generation vehicles will handle: “The main purpose of this essential research program is to build autonomous systems that help the Army effectively execute multidomain operations,” Fossaceca says.

“We don’t want soldiers to be operating these remote-controlled vehicles with their heads down, constantly paying attention to the vehicle in order to control it. We want these systems to be fully autonomous so that these soldiers can do their jobs and these autonomous systems can work as teammates and perform effectively in the battlefield.” (Figure 1.)

Fossaseca notes that vehicles designed for military use face very different operating conditions than self-driving cars for commercial use. Makers of commercially available self-driving cars tend to design for operation on pristine roads, with traffic and pedestrians the major obstacles. Military autonomous vehicles, in contrast, must plan for environments that are much more diverse, including areas that may not even have a road.

“Soldiers may have to operate in forests or deserts, or in a certain manner like moving stealthily in order to achieve some objective,” Fossaceca says. “This is very different than what’s happening in the autonomous vehicle industry, which is the main model of autonomy available today in terms of autonomous vehicle research.”

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MILITARY EMBEDDED SYSTEMS

Figure 1 | U.S. Army photo.

Behind the drive to true vehicle autonomy, Fossaseca says, is ARL’s work to improve the autonomy software stack, a collection of software algorithms, libraries, and software components.

The software stack – originally the work product of the ARL’s now-completed 10-year Robotics Collaborative Technology Alliance – consists of programs that allow autonomous vehicles to perform functions such as navigation, planning, perception, control, and reasoning. The autonomy software stack also contains a world model that the intelligent system can use as reference.

Occurring in parallel right now are two lines of effort (LOE): LOE 1 is work on basic mobility, while LOE 2 involves improving the software’s decision-making ability, which encompasses collaborative learning and advanced reasoning.

“These are happening at the same time and teams run experiments every six months,” Fossaseca says.

Next up for the researchers: Creating a single platform that will first perform narrow AI, or algorithms that can complete very specific tasks consistently and then use these capabilities to multitask under complex conditions. Longerterm, the AIMM researchers are working on the Scalable Adaptive and Resilient Autonomy (SARA) program, which leverages external collaborators outside of the laboratory to accelerate the pace of emerging research on autonomous mobility and human-machine teaming. www.mil-embedded.com

BEHLMAN LEADS THE PACK AGAIN! FIRST PROVEN VPX POWER SUPPLIES DEVELOPED IN ALIGNMENT WITH THE SOSA™ TECHNICAL STANDARD

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MIL TECH INSIDER

Leveraging secure commercial routing technology to protect data-in-motion

By Mike Southworth An industry perspective from Curtiss-Wright Defense Solutions Protecting a military platform’s secret data-in-motion as it’s routed over an Ethernet-based IP network has become significantly easier, more affordable, and faster to deploy in recent years, thanks to U.S. National Security Agency (NSA) support of commercial encryption technologies.

Specifically, the NSA’s Information Assurance Directorate (IAD)’s Commercial Solutions for Classified (CSfC) program enables cost-effective commercial products to be used in layered solutions to protect National Security System (NSS) data classified as secret.

This approach makes it far less burdensome to secure embedded network communications onboard an aircraft, vessel, or ground vehicle, since integrators can use a layered commercial solution based on public cryptography and secure protocol standards (as opposed to considering NSA Type 1 devices only).

In the last few years, the NSA replaced the Suite B algorithms – in use since 2005 for protecting classified and unclassified NSS – with new algorithms included in the Commercial National Security Algorithm Suite (CNSA Suite) as part of its plans for transitioning users to quantum-resistant algorithms.

CSfC requires the use of two encryption layers, which can be both hardware, both software, or a mix of the two. System integrators can select approved commercial components from the NSA Central Security Service (CSS) Components List (https://www.nsa.gov/ resources/everyone/csfc/components-list/), which shows approved cybersecurity solutions, enabling system designers to speed their system development.

Originally, CSfC’s Manufacturer Diversity Requirements insisted system integrators select each of the two encryption layers from two separate vendors. That rule has been updated and now permits “single-manufacturer implementations of both layers,” under specified conditions when manufacturers can prove sufficient independence in the code base and cryptographic implementations of the products used to implement each layer.

To date, Cisco is the only supplier with data-in-motion products on the CSfC-approved components list that can be used to implement both the first and second layer of encryption to satisfy CSfC requirements. Pairing a secure Cisco router and Cisco firewall, each leveraging diverse code bases, can satisfy the requirement for two layers of security.

Cisco’s newest embedded router card, the ESR-6300, is currently undergoing rigorous testing and will obtain all appropriate certifications for military use cases later this year, including FIPS 140-2, Common Criteria and CSfC compliance. It provides support for next-generation encryption (NGE) and quantum computing resistant (QCR) algorithms such as AES-256, SHA-384, and SHA-512 CNSA encryption. Based on enterprisegrade Cisco IOS-XE software, it provides routing and switching security features for highly secure voice, video, and data communication. IOS-XE has been validated on other Cisco platforms for both Common Criteria and CSfC. An example of a product that integrates Cisco’s ESR-6300 module and IOS-XE software is Curtiss-Wright’s rugged COTS Parvus DuraMAR 6300, a small-form-factor secure network router system housed in an chassis optimized for harsh military and civil vehicle/

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MILITARY EMBEDDED SYSTEMS

Figure 1 | Curtiss-Wright’s Parvus DuraMAR 6300 features Cisco’s ESR-6300 module and IOS-XE software to provide a small-form-factor secure network router system.

aircraft installations. (Figure 1.) Its miniature IP67-rated fanless enclosure features military-rated circular connectors and provides six GbE ports, including two routed (WAN) and four switched (LAN) interfaces, providing up to 10 times the routing/switching bandwidth and up to 20 times faster encrypted bandwidth than legacy Cisco ESR-5915-based routers.

The unit also has new capabilities for Cisco IOx (IOS+Linux)- based edge computing services with optional SSD, USB, and serial interfaces to leverage onboard computing resources to analyze, secure, and share data from embedded Internet of Things (IoT) sensors.

In addition to network routers and firewalls, the CSfC list also includes MACSec devices, which provide strong Layer 2 cryptography for point-to-point authentication and encryption for Ethernet traffic between computers and switches on a local area network (LAN). IPsec [internet protocol security] is used to encrypt Layer 3 IP packets for WANs while MACSec encrypts Layer 2 Ethernet frames for LANs. MACSec support was added to the mainline Linux kernel (Kernel 4.6) in 2016, and its adoption is growing. Cisco’s ESS-3300 embedded services switch is a MACSec device that’s been validated for FIPS 140-2, Common Criteria, and CSfC. Mike Southworth is product line manager for Curtiss-Wright Defense Solutions.

Curtiss-Wright Defense Solutions www.curtisswrightds.com www.mil-embedded.com

DEFENSE TECH WIRE NEWS | TRENDS | DoD SPENDS | CONTRACTS | TECHNOLOGY UPDATES

By Emma Helfrich, Associate Editor

Small telescopes for nanosatellites subject of research and development agreement Lawrence Livermore National Laboratory (LLNL) and Tyvak NanoSatellite Systems (Irvine, California) have reached a cooperative research and development agreement (CRADA) to develop innovative compact and robust telescopes for nanosatellites; it is hoped that in the future small satellites will use the advanced optical imaging payloads to collect information for remote sensing data users. The four-year, $2 million CRADA will combine LLNL’s Monolithic Telescope (MonoTele) technology with Tyvak’s approach to fabrication, which simplifies spacecraft design and shrinks spacecraft size, weight, and power needs.

Figure 1 | A space telescope, an identical twin to the one pictured, flew on an LLNL mission to demonstrate the utility of nanosatellites for space situational awareness. Photo: Julie Russell/Lawrence Livermore National Laboratory

According to information from Tyvak, the small (from 1 to 14 inches) MonoTele space telescopes provide imaging for nanosatellites, which are about the size of a large shoebox and weighing less than 22 pounds; and microsatellites, which are about the size of a dorm refrigerator and weighing up to several hundred pounds.

SharpEye radar systems chosen for Lithuanian border surveillance HENSOLDT UK, the manufacturer of Kelvin Hughes SharpEye radar systems, announced that the Lithuanian State Border Guard Service (SBGS) has selected variants of the company’s SBS-900 X-band SharpEye long-range coastal surveillance radar to ensure the safe management and monitoring of vessels in the coastal waters of Lithuania.

According to company officials, HENSOLDT UK’s shore-based radars were specifically developed to meet the operational requirements of port, harbor, and river traffic operators as well as government agencies responsible for the protection of coastal and littoral zones. Working with the local integrator, Telekonta, the mast-mounted SBS-900 were selected to meet the requirements of the Lithuanian SBGS for detection of small targets at long ranges, in accordance with the regulations of the IALA, an intergovernmental organization that advises on nautical matters and uses.

Sharklink communications system to be delivered to U.S. Navy Cubic Corporation announced its Cubic Mission Solutions (CMS) business division won a sole-source, five year contract worth approximately $9 million from Naval Information Warfare Systems Command (NAVWAR) for the production of Communication Data Link System – Technical Refresh (CDLS-TR) equipment. Under the terms of the contract, Cubic will deliver its Sharklink system for use on two aircraft carriers. Sharklink is designed to be a surface data terminal that supports secure, long-range, high-data-rate communications with airborne and shipboard platforms.

Sharklink, the company says, is designed with a flexible architecture to support growth for up to eight simultaneous links and a software-defined radio architecture to support current and future waveforms planned for use by the U.S. Navy. Sharklink’s real-time data is aimed at enabling ships to get the information they need for operations ranging from humanitarian relief to surface combat.

12 July/August 2020

MILITARY EMBEDDED SYSTEMS

Figure 2 | The Cubic Sharklink high-performance surface data terminal supports secure, long-range, high-data-rate communications with airborne and shipboard platforms. Photo: Cubic.

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Autonomous underwater vehicle completes four-year circumnavigation of Atlantic Ocean Teledyne Marine announced that its “Silbo” Slocum G2 Glider – an autonomous underwater vehicle (AUV) manufactured by Teledyne Webb Research – has completed an over four-year journey during which it circumnavigated the Atlantic Ocean in four legs, a first for an AUV. Launched in spring 2016 from Cape Cod, Massachusetts, Silbo collected scientific and critical engineering data along the way for a variety of programs, and returned to Cape Cod in late June of 2020, having sustained no damage save that of a scratched hull.

Figure 3 | The Teledyne Slocum G2 Glider – dubbed Silbo – circumnavigated the Atlantic Ocean in four legs over four years. Photo: Teledyne Marine.

Silbo has served as a test bed for many new engineering hardware and software features for both existing and next-generation Slocum gliders. Glider AUVs – while basic to several major ocean-monitoring programs including the international Argo array and the National Science Foundation Ocean Observatories Initiative, are also part of the U.S. Navy Littoral Battlespace Sensing – Glider (LBS-G) program of record.

AI-driven cloud platform to bolster Air Force threat intelligence

Raven UAS to receive avionics, data link upgrades under $21 million Army contract

Geospark Analytics – which develops applied artificial intelligence (AI) solutions for risk and threat intelligence – won a Special Phase II Small Business Innovation Research (SBIR) contract from the U.S. Air Force (USAF) AFWERX. This latest SBIR award is the fourth for Geospark Analytics’ Hyperion cloud-based platform that is designed to provide analysts and operators situational awareness and an AI-driven forecast of political, economic, and social risk across the globe.

Unmanned aircraft system (UAS) company AeroVironment has announced that the U.S. Army exercised the first of three options under the sole source Flight Control Systems (FCS) domain of the Army’s multiyear small UAS contract. The initial contract option – valued at $21.05 million – includes avionics and data link upgrade packages to modify radio frequencies (RF) used by the Army’s existing fleet of Raven tactical UAS. The Army exercised the option under the FCS domain awarded to AeroVironment by the Army in June 2019.

With this contract in place, Geospark Analytics will aim to extend the Hyperion mobile application with collaboration capabilities intended to streamline the sharing of threat information and analysis between flight crews and Air Force Intelligence, Surveillance, and Reconnaissance (ISR) and Operational Support (OS) units.

AeroVironment’s hand-launched Raven UAS – weighing just 1.9 kg (4.19 pounds) and having an operational range of 10 km (6.2 miles) – is designed, say company officials, for rapid deployment and high mobility for operations requiring low-altitude intelligence, surveillance, and reconnaissance. The Raven’s Mantis i23 EO/IR gimbaled payload is equipped to deliver real-time video or infrared imagery to ground control and remote viewing stations.

USAF to get first lot of F-15EX fighter aircraft from Boeing in deal nearing $1.2 billion The Department of the Air Force has awarded a contract to Boeing – worth nearly $1.2 billion – for its first lot of eight F-15EX fighter aircraft, which uses open mission systems architecture to enable the rapid insertion of new technologies intended to keep the aircraft viable for decades to come. The F-15EX will replace the oldest F-15C/Ds in the service’s inventory; the Air Force plans to purchase a total of 76 F-15EX aircraft over a five-year program.

“The F-15EX’s digital backbone, open mission systems, and generous payload capacity fit well with our vision for future netenabled warfare,” said Dr. Will Roper, assistant secretary of the Air Force for Acquisition, Technology, and Logistics. “Continually upgrading systems, and how they share data across the Joint Force, is critical for defeating advanced threats. F-15EX is designed to evolve from day one.” www.mil-embedded.com

Figure 4 | The F-15EX fighter aircraft uses open mission systems architecture intended to keep the plane viable for decades.

Photo: U.S. Air Force.

MILITARY EMBEDDED SYSTEMS

July/August 2020 13

SPECIAL REPORT

Are satellites a cyberwarfare target?

By Sally Cole, Senior Editor

Spoiler alert: Yes, they are – as militaries increasingly rely on satellites, especially in the age of guided munitions and hypersonic weapons, it’s becoming critical to protect space assets from cyberattacks.

Satellites rely on connected technologies within the cyber realm, including software, hardware, and digital components, which makes them vulnerable to cyberattacks.

14 July/August 2020

Cyberwarfare Technology

One of the main reasons cyberattacks on satellites are a growing concern is because they’re such a stealthy and low-cost way to inflict devastating damage.

As you can imagine, this is problematic for the U.S. Department of Defense (DoD) and all other militaries that increasingly rely on satellites for space imagery and weather maps, communications and positions, intelligence gathering and surveillance, navigation and timing data, not to mention guided munitions.

A NATO report released a year ago, “Cybersecurity of NATO’s Space-based Strategic Assets,”1 by Beyza Unal, put it this way: Almost all modern military engagements rely on space-based assets. During the U.S.-led invasion of Iraq in 2003, 68% of U.S. munitions were guided using space-based means (laser, infrared, and satellite). This percentage was up sharply compared to the first Gulf War, where space-based means were used 10% of the time in 1990 and 1991.

Additionally, in 2001, 60% of the weapons used by the U.S. within Afghanistan were precision-guided munitions..

What’s vulnerable?

Three primary segments are at risk when transmitting satellite data: an uplink (space segment), downlink (ground segment), and crosslink (user).

Electronic warfare (EW) methods are known for their ability to knock out communication signals both to and from satellites. But during a cyberattack, it’s

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possible for hackers to gain full access to satellites and their data; such an intrusion puts the hacker in control and allows them to inflict all kinds of damage.

Figure 1

The most common cyberthreats to the space segment, ground segment, and space-link communication segment, according to the Consultative Committee for Space Data Systems, are data corruption and modification, ground system loss, interception of data, jamming, denial of service, spoofing, replay, software threats, or unauthorized access.

A major part of the problem today is that no one appears to know the full extent of the cyber vulnerabilities of NATO members’ space-based assets and strategic systems. Equally frightening: Any vulnerability within their space infrastructure can potentially spread to other domains.

This situation is especially concerning as the U.S. DoD and other militaries increasingly take advantage of commercial satellites, which aren’t particularly known for emphasizing cybersecurity.

At this point, cybersecurity standards don’t really exist for commercial satellites yet; many don’t even bother to use data encryption.

Protecting space assets is becoming increasingly important because EWbased and cyberattacks are on the rise within military operations. And if you don’t know where your vulnerabilities are, it’s pretty difficult to protect against intrusions or attacks.

Hack-a-Sat competition With all of this as a backdrop – and given the importance of satellites and other space assets to the U.S. military – governmental cybersecurity is starting to attract some much-needed attention and help from the outside the military.

To get people thinking about how vulnerable satellites and space assets are, and to promote education and collaboration within this realm, the U.S. Air Force and the Defense Digital Service (DDS) – which calls itself “a SWAT team of nerds established by the Secretary of Defense www.mil-embedded.com

U.S. Army Cyber Command soldiers work on a project alongside the Defense Digital Service (DDS) personnel at the DDS workspace in Augusta, Georgia. Photo: U.S. Department of Defense.

to provide the best in modern technology to bolster national defense” – decided to launch a space security challenge: Hack-a-Sat, via DEF CON 28’s Aerospace Village [held virtually August 7-9, 2020 (due to Covid-19)] to showcase their mission. (Figure 1, DDS team with Army colleagues.)

DEF CON’s Aerospace Village is run by a volunteer team of hackers, pilots, and policy advisors from both public and private sectors, with the shared goal of providing the flying public with safe, reliable, and trustworthy air travel. All of these factors depend on secure aviation and space operations. There’s also a focus on cybersecurity education and awareness in arenas ranging from airports and air-traffic control to aircraft and spacecraft.

It’s important to note that Hack-a-Sat is an important evolutionary step forward for the U.S. military – in the past it had attempted to go it alone cybersecurity-wise – and is a great way to encourage security researchers (more colloquially known as hackers) to become more engaged in collaborative aerospace cybersecurity.

Hack-a-Sat is a two-part satellite hacking challenge designed to focus security researchers’ skills and creativity on aerospace system cybersecurity challenges. The event includes an online qualification event (which was held in May 2020) and a final virtual event at DEF CON 28 in August.

“Space is now a critical part of our infrastructure and it needs to be protected. All critical infrastructure is an attractive target and, as space is increasingly used, it’s a safe assumption that adversaries will try to exploit it,” says Pete Cooper, director of DEF CON 28’s Aerospace Village. “All involved stakeholders are working hard to increase its resilience, and we’re doing our bit by bringing the community together to help them build trusted relationships.”

The Aerospace Village is encouraging collaboration and the sharing of the knowledge of all aerospace systems – via workshops, talks, and other activities – to figure out where cybersecurity challenges exist and how to work together to solve them.

During Hack-a-Sat’s final event, participants are challenged to reverse-engineer representative ground-based and on-orbit satellite system components to overcome planted “flags” or software code. The contest may contain realistic spacecraft systems,

MILITARY EMBEDDED SYSTEMS

July/August 2020 15

SPECIAL REPORT

Cyberwarfare Technology

and teams are encouraged to prepare for challenges associated with communicating with an orbital asset, including scheduling communication passes.

... the U.S. Air Force and DDS are appealing

The top three teams to overcome the most flags in the Hack-a-Sat will win prize money – $50,000 for first place, $30,000 for second, and $20,000 for third – for their contributions to the research community.

to the broader security-

One of the most surprising aspects of the Hack-a-Sat program for the Air Force so far is simply seeing how much the security research community has rallied around their challenge: “More than 6,000 individuals and more than 2,000 teams registered for the qualification round,” says DeliaRae Jesaitis, strategic communications specialist for the Air Force Research Lab. “We’re excited to see so much enthusiasm and collaboration with experts across the space and cyber domain. Seasoned hackers were scouting experts with a background in astrophysics, and it has brought a completely new dynamic to the traditional capture-the-flag skill set and environment.”

are willing to approach

So why did the U.S. Air Force and DDS decide it was time to invite nonmilitary hackers to (ethically) target a satellite? “Security and resiliency in space systems isn’t a concern unique to the U.S. military,” Jesaitis explains. “The world relies on satellite capabilities for global navigation, communication, and electronic transactions, among other things, and so together we need to ensure these systems are resilient against cyber threats.”

Jesaitis views the collaboration at this event as the key to tackling the cybersecurity challenge for the space domain in the future. “By opening this challenge up to the expansive community that understands both cybersecurity and the space domain within a public environment where barriers to the technology are lifted, researchers are enabled to investigate the system’s security posture through the use of nontraditional creative techniques,” she adds.

From all sides Protecting satellites from hackers is an enormously daunting task – primarily because so many attack surfaces are involved. Attackers can target computer software not only within the satellites and their payloads, but also at their ground stations, communications links, factories where they are designed and built, or even their launch vehicles.

“Satellites pose an assortment of cybersecurity challenges,” says John Marx, senior computer engineer, Air Force Research Lab/RI and liaison to the 16 AF. “A satellite bus is a collection of physical systems running within an entirely remote and resourceconstrained environment, equipped with sensors that take in raw data from many external sources.”

Commercial technology is faster than ever on the ground, Marx points out, but satellite hardware tends to lag significantly behind the technology that exists on the ground. “Software updates on a system are risky, but the nature of it being in space makes it much harder to roll back an unsuccessful update, which can put a multimillion or billion-dollar investment at risk,” he says.

Challenges associated with securing the satellite bus, combined with satellites being controlled from ground stations with the same cybersecurity challenges of any other networked system, “makes protection a multifaceted task,” Marx says. “The complexity of these challenges is exactly why it is so important for us to be working with a diverse group of innovators.”

research com­munity to become allies who the space challenges of tomorrow in an open and collaborative way. the security knowledge gap between the space and cybersecurity domains to incentivize innovation, so we hope to do that,” Jesaitis says.

The U.S. Air Force wants “to be a force multiplier in bringing together two typically disparate communities so that collectively they can help us tackle the unforeseen security risks within space systems and, ultimately, shape how these systems are designed in the years to come as the space domain continues to proliferate,” Jesaitis explains.

By launching efforts like Hack-a-Sat, the U.S. Air Force and DDS are appealing to the broader security-research community to become allies who are willing to approach the space challenges of tomorrow in an open and collaborative way.

“We want to connect stakeholders across the aerospace domain so that cybersecurity experts and aerospace system engineers are working together to build resilient and secure systems at the onset of the system design,” Jesaitis says. “By enabling this type of collaboration, we intend to learn from the community and change how the DoD and DAF acquire, secure, and integrate our technologies.”

We can expect to see more of these military efforts to collaborate with the hacker community. MES Note

Link to the NATO report: https://www.chathamhouse.org/ sites/default/files/2019-06-27-SpaceCybersecurity-2.pdf

1

Bridge the knowledge gap What kinds of things does the U.S. Air Force hope to learn through the competition? “Hack-a-Sat is a joint effort between the U.S. Air Force and DDS to bridge

16 July/August 2020

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MIL TECH TRENDS

Rugged Computing & Thermal Management

Hot problems: Designing a thermally optimal data-acquisition unit

By Pat Quinn

Flight test instrumentation (FTI) data-acquisition systems (DASs) use data-acquisition units (DAUs) distributed throughout an aircraft, often in tight spaces, which drives demand for smaller chassis. In parallel, the demand for higher DAU performance is on the rise, resulting in more heat-generating components packed tighter together.

Since chassis act as a heat sink for the components inside, a smaller chassis provides less metal to drawing heat away from the components.

18 July/August 2020

In order to properly understand the accuracy of a flight test instrumentation (FTI) measurement, the designer needs to know the measurement accuracy for the temperature of the electronics. Electronics expected to perform in more extreme temperatures will be tested, and certified, over a range (typically -40 °C to 85 °C for rugged aerospace electronics). It’s therefore good practice to check the details of accuracy claims by manufacturers because of the possibility that a best-case specification has been cited that may not match performance in realistic conditions.

Heat also ages hardware. Even if systems are operating to a target specification, if they are running hot, their effective lifetime is reduced. An approximate estimate is that a 10 °C increase halves the lifetime of the component (via Arrhenius equation, a formula for the temperature dependence of reaction rates). In reality, while system failure is more complex than the lifetime of components, it is still important, especially when high temperatures are involved.

Effective life should be considered, since a low initial data-acquisition unit (DAU) cost may end up more expensive in the long run if the item requires more frequent replacement.

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Material Carbon steel

Heat Conduction (k) 30-60

Stainless steel

15

Aluminum

263

Titanium

22

Glass

1

Table 1 | Thermal conductivity of some common materials used in DAUs and aircraft.

Figure 2 | Heat sinks are effective for removing heat but are often impractical for ultracompact systems due to their size.

Dissipating heat in FTI systems Which heat dissipation methods are used in existing FTI systems generally depends on the age of the installation and the size of the aircraft. For example, older DAUs tend to be relatively large and bolted to metal in an aircraft made primarily of metal, which enables good conduction cooling from the DAU and – assuming a good design – from the components in the DAU to a larger metal chassis. There may also be some open space that enables decent convection cooling. (Figure 1.)

Some DAUs are placed in racks that use passive or forced air cooling (usually only an option in large aircraft). These benefit from good convection cooling as well as some conduction in the rack. The trend towards smaller chassis located in tight spaces, sometimes on composite structures, makes it increasingly difficult to dissipate heat from the DAU components. (Figure 2.) This reality makes it critical to properly understand and implement good thermal-design decisions in DAUs to meet current and future FTI DAU requirements.

Optimal thermal design Generally, DAU components are mounted on printed circuit boards (PCBs). Several thermal-design decisions should be followed for optimal operation: At a high level, it is important to ensure that heat can be quickly transferred away from components and that heat isn’t concentrated in any one spot.

Increasing heat in flight test instrumentation Since the DAU chassis acts as a heat sink for the components inside, a smaller chassis means less metal to draw the heat away from the components. This situation is compounded by the trend for higher channel densities. What’s more, increases in throughput and channel count require more power to be drawn into a chassis, generating even more heat. Today, many aircraft use composite materials in the airframe, which are significantly less thermally conductive than metal. For example, the thermal conductivity (k) of fiberglass is ~ 0.04 vs. 236 for aluminum (in SI units of watts per meter-kelvin (W·m−1·K−1) at 0 °C). This means a DAU is unable to use conduction cooling as effectively as before; the lower the k value, the poorer the material is at conducting heat. (Table 1.) www.mil-embedded.com

Flight test DAUs typically consist of a chassis and modules. It is important that there is a good method of moving the heat away from the modules in order to help the chassis move heat away from components. In this way, the chassis itself acts as a heat sink. How effective this function is depends on a few factors such as how the chassis is constructed, the quality of the thermal contact between the chassis and its modules, and how power is used in the chassis. There are generally two methods of constructing chassis, either using a solid chassis and separate modules or using a “slice-of-bread” design.

Figure 1 | DAU heat dissipation is typically accomplished using conduction, convection, and radiation.

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A solid chassis has slots in which modules can be inserted, similar to inserting disk drives into a recorder. In the slice-of-bread method there is no separate chassis.

Instead, the chassis is constructed out of the acquisition cards themselves, connecting several acquisition cards together, and securing them via a locking mechanism.

This reduces the power drawn and heat generated, as well as the power supply size. Voltage conversion can instead be performed on the modules.

A solid chassis has the advantage of being a large piece of contiguous metal that enables heat to quickly flow from a hotter region to a cooler one. A disadvantage of the solid chassis is that insertion and removal of modules makes it difficult to create a perfect thermal contact between the modules and the chassis. A slice-of-bread approach has the advantage of being able to very tightly connect the PCB to the chassis, as the chassis is part of the module. The disadvantage of this approach is that it is difficult to create a fully conductive seal between the modules.

Whisk the heat away The Axon DAU is an example of how to design a power-wise and thermally efficient compact data-acquisition unit. A dual side-rail system is used to closely couple the Axon module to the chassis, while still damage-free module removal.

A solid chassis, milled from a single block of aluminum, minimizes any gaps that could lead to hot spots; aluminum’s excellent thermal properties ensure quick heat transfer away from the modules, without requiring more expensive or exotic materials. The chassis acts like a heat sink attached to a microprocessor in a PC. Within the chassis, use of a single voltage rail allows a single holdup capacitor to be used. This draws less power, ensuring the DAU can effectively deal with common supply voltage variances or interruptions. (Figure 3.)

Whichever chassis design is chosen, it is likely constructed from metal, typically aluminum or steel. Steel is cheaper and stronger than aluminum, so chassis walls can be a little thinner and material costs will be lower. However, aluminum appears a better choice as it is a significantly better heat conductor (k = 236 versus 15) and is lighter and easier to mill. In practice, there is little cost saving for a finished steel chassis, as any size difference is trivial and the superior thermal properties of aluminum help move heat from the chassis into the surrounding environment.

There are also design decisions that can help a DAU better use power. It is common for DAUs to supply multiple voltages to modules as there are different voltage requirements for module operation, sensor excitation, and so on. To avoid data loss in the event of a black or brown out, power holdup capacitors are used in the power supply.

Reducing power supply voltages lowers the number of holdup capacitors required.

OpenSystems Media works with industry leaders to develop and publish content that educates our readers.

5G Drives mmWave Technology Across Multiple Industries

By Analog Devices, Inc. 5G communication systems – now being adopted across industries – benefit from years of research done by defense companies for different applications but similar needs. Defense applications, such as when saving a stranded crew member at sea, benefit from the improved resolution of high-frequency radars that can more clearly resolve objects. Additionally, many of the ICs designed for telecommunications must be inexpensive and available in high volume.

This white paper examines the IC supply chain, how these supply chains are dealing with new requirements, and how mmWave frequencies are used to help solve modern comms challenges.

Read this paper at https://bit.ly/2OXduMI 20 July/August 2020

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Read more white papers: http://mil-embedded.com/white-papers/ www.mil-embedded.com

For the module, a large ground plane is used to help draw heat away into the module side rails. For a traditional DAU, there is a limit on how small a DAU can be shrunk to house a single module; the chassis must also house a transmitter card (to send data via Ethernet, IRIG 106 chapter 4 PCM, or IRIG-106 chapter 7) and a power supply.

Axon DAU backplanes use a serial pointto-point link for each module that provides data and power lines, which enables a unique solution for particularly tight or hot locations (such as wings or engine nacelles): the Axonite chassis, which houses a single module. Axonite is connected to an Axon chassis using a single wire via the serial backplane. To the Axon chassis, the module appears to be internally integrated, but can be located up to 10 meters away in a dedicated Axonite chassis. Axon DAUs integrate I2C temperature sensors for thermal monitoring into all parts, including top blocks, modules, power-supply units,

etc. The sensors provide insight into how hot elements get, which is useful for troubleshooting and data-integrity assurance. MES

Figure 3 | This design maximizes thermal dissipation at each stage to keep the components cool enough without external heat sinks or forced air.

Patrick Quinn is product line manager for Aerospace Instrumentation at Curtiss-Wright Defense Solutions. He holds an Electrical & Electronic Engineering degree from the Dublin Institute of Technology.

Curtiss-Wright Defense Solutions www.curtisswrightds.com

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MIL TECH TRENDS

Bridging the cooling gap in high-speed embedded systems

By Steve Gudknecht and Jordan Sudlow In the high-performance world of VPX for defense applications, aggregate payload power calls for creative strategies when addressing cooling at the chassis level as well. New high-performance applications will demand new inventiveness, if not outright new inventions, in applying and adapting established chassis-level cooling techniques while keeping costs down.

Properly engineered VITA 48.2 chassis using air or liquid assist are capable of cooling payloads far more effectively compared to conduction-cooled-only chassis. These design extensions for 3U and 6U systems enable cost savings in applications which can support air and liquid cooling by leveraging a well-established VITA 48.2 supplier ecosystem.

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Rugged Computing & Thermal Management

Years ago, a certain product manager said to a group of engineers, “Don’t show me a product development schedule with an invention in the middle of it!” That advice comes to mind when developing new VPX systems that enable unprecedented computational power in mission-critical defense applications. With the advent of individual 6U VPX modules that surpass 200 W of dissipated power, traditional conduction cooling approaches for heat removal are being pushed to the limit and with that we see the emergence of the various VITA 48 module level cooling strategies.

Board-level cooling vs. chassis-level cooling Managing heat dissipation in VPX systems tends to divide into two areas of concentration where solutions point to board (VPX module)-level cooling on one hand or to chassis-level cooling on the other. In the former case, much effort has gone into developing the VITA 48 REDI [Ruggedized Enhanced Design Implementations] standard and its underlying module-cooling specifications.

While those specifications require chassis-level supporting infrastructure, their mechanical design addresses heat transfer at the module level. Each one uses cooling methodologies branching from VITA 48.2 (conduction-cooled). Much of the design effort to date has centered around 6U modules versus 3U, since the functional density in larger 6U modules pushes heat-dissipation requirements beyond the point where 48.2 is effective.

Stretching the limits of VITA 48.2 chassis design Most VPX systems use VITA 48.2 conduction-cooled modules due to an established deployment track record. As module power continues to increase, however, VITA 48.2 struggles to dissipate the attendant heat using straight

MILITARY EMBEDDED SYSTEMS

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Thermal Load Ranges

Primary Variables

Variable Importance**

Ambient Temp

High

Cooling Fin Geometry

High

Thermal Load***

Low End Thermal Load Example****

High End Thermal Load Example****

Low

55 °C ambient, standard cooling fins

55 °C ambient, standard cooling fins

Medium

55 °C ambient, standard cooling fins, low power fans

30 °C ambient, enhanced cooling fins, high power fans

High – Extreme

71 °C ambient, standard cooling fins, PAO fluid, 50 °C inlet temp

30 °C ambient, enhanced cooling fins, EGW fluid, 20 °C inlet temp, enhanced flow rate

Passive conduction 180 – 250 W

Air over conduction (AoC) 400 – 650 W

Ambient Temp

High

Cooling Fin Geometry

Medium

Fan Selection

High

Liquid over conduction (LoC)

500 – 1200+ W

Ambient Temp

Low

Cooling Fin Geometry

Medium

Working Fluid

High

Liquid Inlet Temp

High

Liquid Flow Rate

Medium

*Chassis size 3/4 ATR short form factor ** Varies under specific use situations ***Assumes uniform slot loading ****Indicates the relative effectivness of combined cooling strategies

Table 1 | These numbers compare cooling capacity using passive, air-assist, and liquid-assist conduction cooling in six-slot VITA 48.2 3U VPX chassis.

conduction cooling. System designers therefore have two choices: Either move to VITA REDI alternatives or stick with VITA 48.2 and stretch the limits at the chassis level.

The choice is a difficult balancing act between conflicting demands like cost, module availability, chassis design, environment, size, and weight. One thing is almost certain: Whether at the chassis or module level, air or liquid cooling will play a role. Power-hungry modules can leverage one of the thermally advanced VPX REDI standards, such as VITA 48.4 (liquid) or .8 (air), but when these modules are not readily available, the system designer will need to use hybrid cooling strategies using VITA 48.2 modules.

Given their performance record, broad supplier ecosystem, and availability in a wide range of functions, the goal is to get the most out of VITA 48.2 modules.

They use known chassis infrastructure and are far less expensive compared to VITA 48.4/.8 versions that require precision machined conduction-cooling frames supporting inlet and exhaust passages (AFT, .8) and inlet/outlet quick disconnect mechanics (LFT, .4) for heat removal. VITA 48.4 /.8 modules are not widely available in 6U and less so in 3U (which are not addressed by 48.4). The dearth in 3U modules makes systemlevel cooling alternatives for that form factor even more important. www.mil-embedded.com

Hybrid chassis design In 3U and 6U, extending the cooling capacity of VITA 48.2 chassis involves adding air or liquid assist to create hybrid designs that amplify the effect of the baseline conduction hardware. Thermal modeling and empirical data indicate that the cooling capacity in conduction-only chassis can be increased substantially when applying air- or liquidassist options. (Table 1.)

Air-over-conduction design In a VITA 48.2 chassis, heat is conducted away from hot module components through the heat sink and out to the module wedge locks. Using air assist, an air-over-­ conduction cooled (AoC) VITA 48.2 chassis channels air through the chassis side walls in a direction perpendicular to the wedge locks. The chassis side walls contain cooling heat sinks and fans to supply adequate pressure and flow rate. The walled areas form enclosed air chambers isolated from the modules, which envelop the payload section and concentrate air flow. Forced air runs coplanar to heat sink fins, drawing away excess heat. (Figure 1.)

Figure 1 | Example airflow pattern in a conduction-cooled chassis with air assist.

Liquid-over-conduction design Liquid-over-conduction (LoC) VITA 48.2 chassis are used for high-performance thermal requirements where air assist is insufficient, and where the application can support an external pump and chiller. LoC chassis channel the coolant perpendicular to the card edges through system cold plates (chassis side walls) in a fashion similar to AoC chassis. Two popular coolant choices are EGW [ethylene glycol water] and PGW

MILITARY EMBEDDED SYSTEMS

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Rugged Computing & Thermal Management

[propylene glycol/water] mixtures where the glycol additive serves as an antifreeze.

Additionally, PAO [polyalphaolefin] sees popularity among military and aerospace applications primarily due to its dielectric properties. (Figure 2.)

Cold plate design A potential game changer in cold plate design is the rise of 3D printing, also known as additive manufacturing. Cold plates today are typically fabricated by machining the fluid channels into complimentary halves of a plate. The halves are then joined using dip brazing or vacuum brazing. It’s a lengthy and expensive process; moreover, if cold plates are not properly flushed, salts used in the brazing process may contaminate working fluid or be ingested into pumps. In contrast, new 3D manufacturing enables precise location and layout of fluid channels while reducing lead time and costs.

For less rugged applications, a new design approach in producing liquidcooled cold plates involves the use of a primary plate that incorporates integrated gasketing for O-rings, the flow channel, and cooling fins. A bolt-on plate compresses the O-ring gaskets in place. Separate O-rings enclose the channel and encircle retaining hardware in the center. Synthetic rubber O-rings provide service temperatures from -65 °C to 150 °C.

Figure 2 | Example of liquid flow pattern in a conduction-cooled chassis with liquid assist.

Heat sink design Optimal heat sink design for both AoC (air) and LoC (liquid) chassis requires the use of high-power press-style fins that enable higher fin density compared to milling techniques and provide more heat-dissipating surface area than can otherwise be achieved. For AoC applications, cooling fans should be chosen based on flow rate, acoustics, reliability, and static pressure. Forced air passes coplanar to the fin surfaces along the length of the chassis, so fin density must

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be balanced between optimal dissipative capacity minimal air flow resistance.

Temperature sensors regulate fan speed to maintain target temperatures. For LoC applications, typically the chassis is one of many items on the systemcooling circuit which may include a chiller and pump. Chassis design therefore centers on optimizing heat sinks for the predetermined flow rate.

Environmental use cases Air- and liquid-assist designs should maintain card-edge temperatures of 70 °C and 85 °C for standard and extended temperature versions, respectively. The selection is based on the system operating temperature, which can range from -40 °C to 71°C. When determining whether to employ AoC or LoC cooling, both models should be assessed.

AoC cooling is relatively simple and requires little external infrastructure to support chassis operation. Applications for these systems include air, land, and sea assets where space constraints, cabin environments, and altitude can tolerate larger system footprints and air pressure is sufficient for fan cooling.

AoC cooling will, however, see reduced performance during high temperatures and altitudes.

LoC cooling applications for embedded systems are becoming increasingly prominent. Advantages of this method include increased thermal dissipation and higher tolerance with regard to ambient temperature and altitude. For LoC systems, inlet fluid temperature and fluid flow rate largely determine payload temperature. A drawback of liquid cooling is that the system requires external resources including chillers and pumps to provide the coolant; due to these factors, they lend themselves to larger air, land, and sea assets with fewer space constraints.

Liquid closed-loop cooling Chassis suppliers are investigating leading-edge solutions to address the external resource requirements of liquid cooling. Closed-loop chassis, for example, integrate the pump, radiator, and coolant www.mil-embedded.com

reservoir into the control volume of the chassis, eliminating the need for external cooling hookups. The working fluid forms a “closed loop,” which recirculates continuously around the chassis transporting heat away from the hot payload. Early results are promising. MES Steve Gudknecht is the product marketing and communications manager at LCR Embedded Systems. He has more than 15 years of experience promoting and managing solutions for the embedded computing industry. Steve also served as marketing manager for ACT Technico and later for Elma Electronic.

Jordan Sudlow is a mechanical design engineer at LCR Embedded Systems.

Jordan is a graduate of Geneva College and has been with LCR for two years, specializing in VPX chassis design, FEA simulation, and thermal-fluid applications.

LCR Embedded Systems • www.lcrembedded.com

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caption

Can you really simulate an FPGA device?

By Max Taylor-Smith

FPGAs – field-programmable gate arrays – are an incredibly diverse method of extracting multifunctionality from a single piece of silicon. The usefulness of these devices is encouraging a renaissance of their use in military-focused embedded systems as developers scramble to be at the front of the queue for new interoperability contracts in FACE [Future Airborne Capability Environment] and SOSA [Sensor Open System Architecture] systems.

26 July/August 2020

Higher-power FPGA [field-programmable gate array] versions, coupled with continuing reduction in transistor size, ensures there is higher criticality to meet the environmental demands set out in VITA 47, but the approach to thermal solutions has remained relatively stagnant for the last 10 years. The newer generation of size, weight, power, and cost (SWaP-C)-optimized systems simply will not allow for thermal margin built in to deal with inaccuracy.

FPGA structures vary depending on the vendor, but fundamentally they follow the same structure. Basic functional logic elements are connected through programmable interconnections between fixed wires. Figure 1 shows the functional units as gray boxes, I/O elements as white boxes, and wires and programmable interconnects as black lines. The strategic connection of these functional units can replicate larger-scale logic units, such as processors or memory, in an interconnected network on the chip.

In an FPGA most of the delay in the chip comes from the interconnect.

Connecting one functional unit to another functional unit in a different part of the chip often requires a connection through many transistors and switch matrices, each of which introduces extra delay (Zeidman, 2006). Figure 2 shows in more detail the level of switching required to determine connectivity between functional blocks.

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When developing logic using CLBs only, the resultant logic is referred to as “soft blocks,” so named because of their high configurability.

“Hard blocks,” by contrast, are em­bedded functionality on an FPGA that can only be used for a predetermined purpose.

Examples of these could be processors, memory blocks, or high-speed transceivers. These are beneficial in that they have optimized routing and increased logic density enabling reduced timing restrictions, while consequentially reducing the configurability of the chip (Weber & Chin, 2006) and significantly increasing the heat flux density in these dedicated areas (Sundararajan, et al., 2006).

Figure 1 | FPGA structure (Santangelo, 2014)

Logical distribution When a circuit is implemented, the place-and-route tools place critical logic close together and spread other logic as far as allowed by the circuit constraints (Velusamy, et al., 2005). Logic distribution is typically dependent on, and local to, pinout placement because timing restrictions on certain I/O require minimized interconnection length between pin and active logic. This mirroring is not a perfect prediction, however, as not all logic requires these strict timing restrictions, the die size is typically much smaller than the solder balls, communication with other control logic may need more optimal placement, and physical logic must be available and so can divert routing.

Figure 2 | FPGA interconnecting switch method (Zeidman, 2006)

The sheer programmability of FPGAs implies that more transistors are needed to implement a given logic circuit in comparison with custom ASIC [application-specific integrated circuit] technologies. This leads to a higher power consumption per gate and increased power demand per device (Anderson & Najm, 2004).

FPGA shapes and logic The configurability of an FPGA is delivered using large amounts of logic collated into fundamental building blocks called CLBs [configurable logic blocks], formed of smaller components: flip-flops and look-up tables. The allocation and control of signals between these blocks drives the functionality of the FPGA and so position and density of active logic is entirely user-dependent. This situation presents a real challenge to accurate thermal simulation of a device, and using a typical junction to case resistance can give wildly inaccurate results as operability is adjusted to each device.

Designing an FPGA architecture from scratch using only these CLBs is extremely laborintensive due to the high level of functional detail needed for modern computing. www.mil-embedded.com

Software such as Intel’s Quarts Prime or Xilinx’s Vivado Design Suite will handle the majority of this floorplanning and can also offer the user the opportunity to prioritize switching performance, thermal performance, or a balance between the two. Unfortunately from a thermal perspective, however, choosing this focus may significantly affect the latency of an FPGA where some high-density logic is critical to functionality of the device, and this option is rarely available.

Chips heat up in any transistor-based switching device, some power will be lost as heat due to inefficiencies in the device or due to the nonzero resistances to current in a gate (Engineering Entropy,

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2020). This situation is ubiquitous for all semiconductor architecture and creates a requirement for suitable chip- and system-level cooling.

Accurate thermal management of these devices is critical to maintaining the desired operating lifetime of electronic devices, which is exponentially shortened by increasing temperature (V. Lakshminarayanan & N. Sriraam, 2014). Overengineering a thermal solution, ironically, can have a negative impact on a product by increasing undesirable factors such as mass and cost.

Thermal power dissipation in FPGA CMOS transistor devices can primarily be divided into dynamic and leakage – also known as static – power dissipation.

Dynamic losses arise from capacitive charging and discharging of the transistors plus short-circuit power, typically providing the majority of thermal dissipation in an FPGA device.

In legacy FPGAs, dynamic power contributed up to 67% of power usage, with static power providing just 22%. In more recent 28 nm devices, static power has increased its dissipation contribution to closer to 40% of the total thermal loss (Intel FPGA, 2018).

The lack of knowledge of how exactly leakage power is distributed across the chip leads to highly inaccurate power traces, and therefore unreliable thermal estimation (Amouri, et al., 2013).

The dynamic power varies greatly with design and is characterized in detail through vendor power-estimation tools (Intel’s Powerplay Quartus or Xilinx’s XPower, for example). It is a function of the known logic quantity, switching frequency and toggle rate.

P_dynamic=[1/2 〖CV〗^2+Q_ShortCircuit V]f∙activity

( 1)

Where C is the capacitance of the transistor, V is the power rail voltage, QShortCircuit is the power consumed during a change in the CMOS logic gate, f is the net frequency, and activity, or toggle rate, is the average number of signal transitions relative to a clock rate (%).

Leakage power is as a result of the noninfinite resistance across an inactive gate threshold, and is heavily dependent on the device temperature (Kushwaha, et al., 2018). The following equation describes the exponential relationship between leakage power, Pleak, and temperature, T. P_leak=P_0×e^((-k)⁄T)

( 2)

Unlike in an ASIC, logic that is not utilized in an FPGA remains on the device and so remains powered even though not in use, creating a large power demand for a device even with a low logic load.

Static power generally does not vary significantly with logic utilization, but is more greatly dependent on the amount of logic on the die (Intel FPGA, 2018) (Tuan & Lai, 2003). The impetus is therefore on the design engineer to select the smallest device for the given application.

While the design engineer should take steps to ensure that the FPGA has been sized correctly for the functionality desired, it is almost impossible to achieve full utilization in a device due the limited supply of programmable routing resources. Generally speaking, a highly utilized FPGA architecture holds around 75% utilization, which is not an unreasonable estimate given the 62% utilization reported (Gayasen, et al., 2004). This report is slightly dated and it is expected that FPGA technology has developed since then. For an extreme example, Xilinx claims the Ultrascale can accommodate utilization of up to 90% (Xilinx Inc., 2015) although this will be entirely dependent on the desired functionality.

Circuit gating is an additional option commonly used to reduce power (Lach, et al., 2004), whereby blocks of unused logic are “turned off” from the voltage rail until needed and so have no static power draw. This technique has been shown to be used by Xilinx (Xilinx Inc., 2015) and Intel (Intel Corp., 2020) on recent devices.

Where P0 and k are process dependent constants (Amouri, et al., 2013).

Figure 3 | The power distribution in a “real” FPGA circuit (Shang, et al., 2002)

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MILITARY EMBEDDED SYSTEMS

A significant contributing factor to both the dynamic and static power dissipation in an FPGA is the joule heating of the interconnects. Research completed by Shang et al. (Shang, et al., 2002) shows as much as 50% to 70% of the total power dissipated in a Xilinx Virtex-II was from the interconnection network, shown in Figure 3. While the allocation of this loss to the static or dynamic power contribution is not fully determined, it is expected that with the programmable nature of the interconnect switching the majority of this power is concentrated around active logic. www.mil-embedded.com

This high dissipation factor is a result of significantly longer interconnect lengths in FPGAs than ASICs due to the larger area consumed by the logic (Anderson & Najm, 2004). Observing the joule heating and electrical resistivity equations we can identify this relationship: P=I^2 R

( 3)

R=ρL/A

( 4)

where P is power consumed, I is electrical current, R is the wire resistance, ρ is the resistivity of the material, L is the length of the wire and A is the crosssectional area.

Equations (3) and (4) can then be combined to give a linear relationship between the length of and the power dissipated in the interconnect.

P=I^2

ρL/A

( 5)

Finally, the most power-hungry input on an FPGA will usually be the power rail, often denoted as Vcc. This is understandable because the core power rail drives the logic, the use of which is central to any FPGA design (Intel Corp., 2017).

How should I simulate it?

In good rugged system design, the resistance of the heat sink will be dependent on the cooling requirements of the system, including adjacent thermally critical devices, and be both cost- and massefficient. Using a predetermined thermal resistance will not allow for optimization of the thermal solution.

In high-ruggedization environments, such as those set out by VITA-47 ECC4,

The 10% inaccuracy derived from uni­form heat flux thermal models can be significantly improved upon by considering the physical floorplan of each device. Using available software tools and processes, thermal simulation can be tailored not only to a device level, but to an architecture level with a high degree of accuracy. the rack temperature must be set at +85 °C, meaning the junction temperature must be higher than this.

The typical approach to junction temperature distribution Considering the unequal and varied distribution of logic within each individual FGPA architecture, there is inherent inaccuracy in assuming the temperature – and therefore power – in the die can be considered with a single value, or applied uniformly across the surface of the die (Intel FPGA, 2018). This effect is likely to be mitigated with the onset of increased leakage power significance on small transistor dies and with the wide distribution of interconnect heating, but there will inevitably be some variance.

Both Intel and Xilinx provide Delphi and detailed IC models of their FPGAs; however, these are calibrated using a uniform heat flux on the die only. Intel reports that this method gives an average accuracy of only 10% for the resistance of the device (Altera Corp., 2012).

Thermal-design tools Given the variability of factors described above, an accurate thermal simulation can be truly achieved only with a user-guided approach bespoke to each FPGA architecture.

Some research (Amouri, et al., 2013) (Velusamy, et al., 2005) (Huang, et al., 2009) has been completed into how to more accurately predict the temperature variation within the silicon.

W. Huang et al. (Huang, et al., 2004) proposed a modeling methodology, HotSpot, which divides the FPGA die into discrete blocks. Each of these blocks is assigned a thermal resistance generated from the geometry of the block and material properties of the silicon die, and an assigned thermal power. (Figure 4.)

This method has shown tremendous accuracy for temperature distribution, but it does not describe the method of identifying power source and its dependency with temperature.

Figure 4 | Showing the discrete method Hotspot employs to derive local die temperatures (Huang, et al., 2013) www.mil-embedded.com

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To extract much more applicable thermal information for embedded design, Amouri et al. (Amouri, et al., 2013) describe a process which uses the Hotspot methodology for estimating temperature variation, but iteratively calculates the impact of leakage power distribution across the die using the following inputs available from FPGA development tools: ›› Die dimensions (taken from data sheet) ›› A floorplan circuit description of the device ›› A detailed power report This method assumes that the junction has a uniform temp and so leakage power is evenly distributed across the die. It then provides Hotspot with power per block information on the design, which calculates the temperature distribution, which is in turn discretized and fed into a leakage model based on equation (2).

This method is the most complete found in literature research and if implemented correctly will provide a designer with a highly accurate temperature distribution (average error of 1 °C) across a die (Amouri, et al., 2013).

Using the discretized power data, this can be applied to the detailed IC package geometry within a CFD package giving genuine high confidence in thermal simulation results.

What’s a thermal engineer to do?

The 10% inaccuracy derived from uniform heat flux thermal models can be significantly improved upon by considering the physical floorplan of each device. Using available software tools and processes, thermal simulation can be tailored not only to a device level, but to an architecture level with a high degree of accuracy. Thermal engineers should be mindful that while test data has shown these iterative simulation studies can provide an impressive 1 °C of accuracy, there is no validation of power figures at the test stage. These results typically use an off-the-shelf heat sink which is applicable with the given development tools, while more complicated heat sink design should be calibrated against the power estimator results.

Until further validation can be provided and quantified for the true power consumption of an FPGA, a conservative solution should always be evaluated.

For a Xilinx device, this may be as significant as simulating a device at 48 W for a given 40 W power consumption.

Product developers are stuck between a rock and a hard place. MIL-STD-810 is not going to relax its temperature stipulations, and so until more creative cooling solutions such as ultra-high conductivity chassis and/or VITA 48.8 (Air Flow Through) become commonplace, the +85 °C cold wall will remain the driving factor for outstanding product performance. Conversely, more stable semiconductor compounds look destined for the power-electronics and automotive market, meaning embedded designers are stuck with a thermal runoff just as things become difficult. MES

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www.mil-embedded.com

REFERENCES Altera Corporation, 2012. Thermal Management for FPGAs. Altera Corporation.

Amouri, A. et al., 2013. Accurate Thermal-Profile Estimation and Validation for FPGA-Mapped Circuits, Karlsruhe: IEEE. Anderson, J. H. & Najm, F. N., 2004. Power Estimation Techniques for FPGAs. IEEE. Engineering Entropy, 2020. Engineering Entropy. https://secureservercdn.net/160.153.138.53/nm2.751. myftpupload.com/wp-content/uploads/2020/02/3.-What-actually-is-TDP-and-why-is-it-important-3. pdf?time=1589271825 Gayasen, A. et al., 2004. Reducing Leakage Energy in FPGAs Using Region-Constrained Placement, Monterey.

Huang, W. et al., 2004. HotSpot:ACompact Thermal Modeling Methodology for Early-Stage VLSI Design. IEEE. Huang, W. et al., 2009. Differentiating the Roles of IR Measurement and Simulation for Power and Temperature-Aware Design, Boston: IEEE. Intel Corporation, 2017. Understanding and Meeting FPGA Power Requirements. Intel Corp.

Intel Corporation, 2020. Intel Stratix 10 Power Management User Guide. Intel Corporation.

Intel FPGA, 2018. Power Analysis. https://www.youtube.com/watch?v=8y6M-rmz19I Intel FPGA, 2018. Thermal Management in Intel Stratix 10 Devices. https://www.youtube.com/ watch?v=IiX97BwjhyM&t=331s Kushwaha, A., Verma, G. & Kakar, V. K., 2018. Thermal Analysis and Modelling of Power Consumption for FPGAs, Paris: International Conference of Advances in Computing and Communication Engineering.

Lach, J., Brandon, J. & Skadron, K., 2004. A General Post-Processing Approach to Leakage Current Reduction in SRAM-based FPGAs. IEEE. Santangelo, L., 2014. Viv2XDL: a bridge between Vivado and XDL based software, Pisa: University of Pisa.

Shang, L., Kaviani, A. & Bathala, K., 2002. Dynamic Power Consumption in Virtex-II FPGA Family.

Sundararajan, P., Gayasen, A., Vijaykrishnan, N. & Tuan, T., 2006. Thermal Characterization and Optimization in Platform FPGAs. ICCAD. Tuan, T. & Lai, B., 2003. Leakage Power Analysis of a 90 nm PGA. IEEE. V. Lakshminarayanan & N. Sriraam, 2014. The Effect of Temperature on the Reliability of Electronic Components, Bangalore: IEEE. Velusamy, S. et al., 2005. Monitoring Temperature in FPGA based SoCs, San Jose: IEEE. Weber, J. M. & Chin, M. J., 2006. Using FPGAs with Embedded Processors for Complete Hardware and Software Systems. American Institute of Physics.

Xilinx Inc., 2015. Proven Power Reduction with Xilinx UltraScale FPGAs. Xilinx Inc. Zeidman, B., 2006. All about FPGAs. https://www.eetimes.com/all-about-fpgas/

Max Taylor-Smith is the engineering director for Entropy ElectroMechanical Solutions. He has been involved with specialized simulation and management of high-performance electronic devices throughout his career, focusing on embedded systems and hybrid powertrains at Abaco Systems and Mercedes AMG HPP, respectively.

Max is an active participant in VITA Standards Working Groups and ADS’s Special Interest Groups. Readers may reach him at max.taylorsmith@ engineeringentropy.co.uk.

Entropy Electro-Mechanical Solutions https://engineeringentropy.co.uk/

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INDUSTRY SPOTLIGHT

Title Managing the

By John McHale, Editorial Director military’s big data challenge abstract

By Emma Helfrich, Associate Editor

With every second that ticks by, the amount of data gathered by the U.S. military grows, as does the desire and need by the U.S. Department of Defense (DoD) to extract and use this data to form actionable intelligence. This situation directly results in an intense demand for military technology manufacturers The to quickly produce both software and hardware capable of first processing the zettabytes of data that exist on Internet of Things (IoT) devices and then accurately analyzing its value. Successful gathering, processing, and analyzing will effectively change warfare as it is understood today.

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caption

The digital age, the age of information, the computer age – all are terms used as identifiers to depict how the 21st century has brought with it nearly unfathomable amounts of data. Knowing that the information is there and how to access it is one thing, but making sense of it and using it for both defense and commercial purposes is what makes it so-called big data.

The challenge for both warfighters and the manufacturers that provide them with their technology: Acquiring that data in contested environments and relaying it in an efficient way. Making this task more difficult is the reality that conflict often occurs in data-denied areas, making it near-impossible for these systems to access the information the military wants or doesn’t yet know it needs.

Big data and the military “The accessibility of data in-theater is a key challenge for advancing big data utilization in the military,” says Chris Sloan, chief offering manager at National Instruments (NI – Austin, Texas). “Operational security, hardening against ­vulnerabilities, and ultra-high reliability can factor in driving designs incorporating autonomous isolation with little connection to the outside world, which are factors at odds with the free-flowing world of big data. However, there are many creative ways to utilize big data while maintaining autonomy and protections of deployed assets. For instance, at NI, we are investing in our digital ecosystem to enable the linking of data produced through design, production, and field testing of systems so that data can be collected and analyzed outside data-poor environments.

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of having limitations based on limitations of the available data that can lead to inappropriate responses in novel situations, and it isn’t clear which systems are vulnerable to what kinds of novelty,” Reilly asserts. “Developing data-driven systems that can be validated to the extent necessary for deployment in real-world, military contexts is a major challenge for the community.”

The Five Vs of big data – akin to the who, what, where, when, and why of journalism – constitute its meaning.

Volume, velocity, variety, veracity, and value act as the road map for taking full advantage of the digital memory that exists across global data­bases. The last of the Vs, value, is used to further emphasize that without the capabilities to structure that data, it’s essentially useless.

A good starting point for overcoming the problems presented by using big data in military applications is to understand what exactly makes the data so big in the first place.

The Five Vs The Five Vs of big data – akin to the who, what, where, when, and why of journalism – constitute its meaning. Volume, velocity, variety, veracity, and value act as the road map for taking full advantage of the digital memory that exists across global databases. The last of the Vs, value, is used to further emphasize that without the capabilities to structure that data, it’s essentially useless.

“Big data is a broad term with applicability across many areas of interest to the military,” Sloan states. “We see a clear trend of military requirements directing the use of big data throughout the life cycle of new procurements and the modernization of legacy systems. As new sources of data develop and novel uses for data emerge, big data growth will continually outpace utilization in all industries, including the military. We don’t see this as a limitation, but rather a forcing function that will drive innovation.”

“While it’s true that commercial applications and game systems have acknowledged this challenge and apply big data in creative ways, these industries do not operate the in life-and-death environments that warfighters deal with daily,” says Dr. Scott Neal Reilly, senior vice president and principal scientist at Charles River Analytics (Cambridge, Massachusetts).

“In particular, systems that are learned from data instead of designed have the risk www.mil-embedded.com

“We agree that collecting sufficient volumes of data (the first V in the big data model) is essential but will provide no valuable outcome without the other Vs in the chain,” Sloan says. “When it comes to the second V, velocity, the definitions of ‘timely’ and ‘efficient’ can vary greatly, depending on the particular application.

Some applications will require real-time processing of data during the execution of a process, while in other cases, timely and efficient may mean getting results within hours or days instead of the months or years it might take for a human to manually determine. NI is focusing on software-enabled automation combined with reusable and configurable system architectures to greatly reduce the time and effort required to transform collected data into actionable information.

“Moreover, our driving big data philosophy is to use software automation to drive velocity through the remaining Vs – variety, or automating the association and linking of disparate data sources; veracity, or automating data cleansing and statistical significance throughout the processing chain; and value, or converting the initial volume of data into useful outcomes by enabling advanced analytics,” he adds.

The roles of AI and ML Artificial intelligence (AI) and machine learning (ML) play pivotal roles when it comes to analyzing the value of collected data. Sifting through the seemingly endless sea of digital information is a task that has proven too arduous for the human warfighter, but one that can be completed in seconds with an AI-powered algorithm.

“The DoD AI strategy is prioritizing systems that reduce cognitive overload and improve decision-making,” says Michael Rudolph, aerospace and defense industry manager for MathWorks (Natick, Massachusetts). “In order to speed up that OODA [observe, orient, decide, act] loop, AI needs to make earlier predictions and identify

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emerging issues from a variety of data sources. With big data in AI, the question is not just how much data but one of data and feature quality.” (Figure 1).

Big data has been called the oxygen of the ML revolution and military intelligencegathering. The capabilities are designed to supplement each other with the intent to provide warfighters with mission-critical, timely information at the tactical edge.

ARTIFICIAL INTELLIGENCE

MACHINE LEARNING

Any technique that enables machines to mimic human intelligence

Statistical methods that enable machines to “learn” tasks from data without explicitly programming

DEEP LEARNING Neural networks with many layers that learn representations and tasks “directly” from data

Deep learning more accurate than humans on image classification FLOPS

1950s Thousand

1980s Million

2015 Quadrillion

Figure 1 | The evolution from artificial intelligence to deep learning, considered in terms of computer performance over time. MathWorks chart.

“Highly successful predictive analytics and machine learning applications are data-hungry, require years to develop, and can amass substantial code complexity in the first operational version,” says Robert Hyland, director of program transition and principal scientist at Charles River Analytics. “We see significant promise in new programming techniques such as probabilistic programming languages (PPLs) that feature data set probability distributions as first-class programming features, among other programmer affordances.

“PPLs also help reduce the size and complexity of predictive systems,” Hyland continues. “For example, the United Nations ML system for seismic monitoring required $100 million over several years to develop 28,000 lines of code. Its

BIG DATA, MILITARY SENSORS, AND OPENVPX The military sensor chain generates vast amounts of data – information flows in from ISR [intelligence, surveillance, and reconnaissance] and electronic warfare (EW) tools, with input from signals and communications intelligence activities. The amount of data is so overwhelming that it becomes impossible for human operators to sift through it all.

“If you think about the way that sensor technology continues to advance in the military, there’s exponentially increasing amounts of data,” says Shaun McQuaid, director of product management at Mercury Systems (Andover, Massachusetts). “Whether that’s images with higher pixel counts or video data or electromagnetic (EM) spectrum and capturing larger and larger bandwidths of that simultaneously, at the end of the day all of these sensors actually produce a big data problem for our platforms.”

“There’s always more data available,” McQuaid continues. “And I think it’s becoming increasingly clear that trend is not going to end any time soon. The more that you look at sensors and how they’re growing, the more that you focus on things like pixel count on cameras or infrared imaging. With the amount of work that’s done in the EM spectrum, from defending against electronic attack to jam or spoof or whatever the case might be, the amount of data that’s necessary in order to operate effectively, and the amount of communication that has to happen, is only going to increase. I think that there’s no doubt that the direction we’re going, from a data perspective, is definitely upwards. That’s the trend, I think: more and more and more.”

To facilitate that the glut of information, McQuaid and his colleagues are taking the data center concept used in the commercial world and adopting it for use in military applications via solutions based on the OpenVPX architecture (see photo, above).

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The EnsembleSeries HDS6605 6U OpenVPX blade server with hardware-enabled support for artificial intelligence (AI) applications is aimed at use in advanced C4I processing, autonomous platforms, and smart missions. Mercury Systems photo.

“We’re actually using the data center – so same processes, same fabric, same software, same tools, same everything – uncompromised and putting it into the OpenVPX format,” says John Bratton, product marketing director at Mercury Systems.

The data center is brought to the warfighter because they can’t build it themselves, McQuaid says. “[It] gives them the ability to extract actionable information from that big data stream and provide it in a timely manner to the folks on the platform if it’s manned, or the operators if it’s unmanned, in order to make decisions in real time.”

OpenVPX has built-in advantages for the data center application: “One is that the open architecture of OpenVPX, and investment in those open standards, means that technology refresh can happen much more quickly and in a much more agile manner than they used to in the past,” McQuaid says. www.mil-embedded.com

successor, NET-VISTA, was implemented to peform the same ML function but only required approximately 25 lines of code written in an early PPL, and it cost $400,000.”

Capabilities and advancements like this UN example showcase the symbiotic aspects of big data and ML/AI relationships.

“The capability to effectively do this relies upon big data – data generated by the models and simulations that define the expected behavior, data observed in each component during production testing, and data collected from actual field operating conditions and failures experienced,” Sloan notes.

“Transforming this vast data into meaningful prognostics can require ML for certain functions, such as learning causeand-effect relationships to automatically refine forecasts and alerts.”

Analyzing text data Military intelligence often comes from textual sources, whether smartphone messages, email, social-media posts, documents, and the like. Analyzing this data for keywords, group behavior, and actionable intelligence is a task that is often beyond a human analyst (Figure 2).

Figure 2 | Analyzing military intelligence data for actionable information is often beyond the capabilities of human operators, thereby driving the need for improved artificial intelligence and machine learning methods. Shown: Operations at U.S. Army Cyber Command (ARCYBER) headquarters, Fort Belvoir, Virginia. Photo by Bill Roche.

surely face processing obstacles, having the responsibility for the algorithm that makes sense of the information being processed is an entirely different request.

“We’ve been focused on building out a variety of tools for different types of unstructured data,” says Seth DeLand, data science product manager at MathWorks. “We recently added a new product, Text Analytics Toolbox, that focuses on the analysis and understanding of unstructured text data. Our customers are using it in applications such as sentiment analysis of social-media data, predictive maintenance using mechanic logs, and topic modeling to summarize large collections of text.”

Even with these advancements, engineers know that the big data problem remains.

But the drive to borrow commercial innovation and bring it to the tactical edge is more prevalent than ever, making the big data problem more of a big data challenge. MES

www.interfaceconcept.com

“One important type of unstructured military data is textual documents – like reports, manuals, and websites,” says Dr. Terry Patten, principal scientist at Charles River Analytics. “This data was typically generated for human consumption and is very difficult for machines to process because words often have several meanings and there are many different ways of saying the same thing.

Determining the intended meaning typically requires looking at the context of words in the sentence and the context of the document as a whole. However, there is so much valuable information trapped in textual documents that it is critical to find ways to extract it automatically. Charles River Analytics is developing an approach to extracting meaning from text that is based on sociolinguistic theory and cutting-edge, constraint-solving technology.”

Software companies are taking the brunt of the operational challenges of structuring big data. While hardware manufacturers www.mil-embedded.com

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Since 1987, Interface Concept has been a leading developer and manufacturer of leading-edge HPEC embedded boards and systems for military, aerospace and industrial applications.

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MILITARY EMBEDDED SYSTEMS

July/August 2020 35

INDUSTRY SPOTLIGHT

Addressing the data challenges of modern electronic warfare and radar

By Chris Miller Radar, electronic warfare (EW), and signals-intelligence (SIGINT) systems face new challenges from near-peer threats, requiring multigigahertz bandwidths, nanosecond latencies, and the ability to implement and field new EW techniques – all of them needed to deploy in seconds or minutes, not days or months. Reconfigurable FPGA-based signal processors, optical streaming interfaces based on the Optical Data Interface (ODI) standard, and lowoverhead packet standards based on the VITA Radio Transport (VRT) specification, combine to deliver unprecedented performance and flexibility. These three new technologies converge to enable a new class of software-defined operational and measurement systems that are able to address these new challenges.

36 July/August 2020

Leveraging Big Data for Military Applications

Whether the mission is to intercept and collect, analyze, or counter, the many wireless signals that crowd the electromagnetic spectrum (EMS) – a combination of new technology trends – is increasing the probability of earlier detection, assessment, and response. The EMS on an electronic battlefield is chaotic and complex; the ability to fully understand signal behavior in a real-world environment is crucial in the design and validation of the latest radar, electronic warfare (EW), and signals-intelligence (SIGINT) systems.

Let’s look at a simple example of the current deployed state (Figure 1). When an aircraft detects a radar signal, it goes to its EW system’s look-up table.

Assuming it can identify the signal, the aircraft – or an adjacent one in this case – would correspondingly select an appropriate countermeasure signal to jam it. In development are EW systems that may be able to identify the class of a new, adaptive radar signal. These systems generate a countermeasure signal based on existing techniques that would allow some parameters to be adjusted, such as frequency or the pulse repetition interval (PRI). Unknown threats would still need to be recorded and analyzed in the lab.

Increasingly complex and diverse threats are driving the need for future EW ­systems to identify and neutralize these adaptive radar signals with cognitive countermeasures. As the EW threat environment continues to evolve, confidence and reliability in EW system validation and verification depends on improvements and modernization in the test and evaluation process.

There are several significant measurement challenges, however. First, the signals of interest are highly unpredictable, making them difficult to capture and recreate using traditional measurement methods. Fortunately, the latest digital hardware, processing engines, and interfaces enable the creation of RF [radio frequency] streaming solutions that can analyze, record, and play back signals for seconds, minutes, hours or even days. Another challenge is the resulting mountain of “Big Data”: Dealing with a glut of data calls for an optimized

MILITARY EMBEDDED SYSTEMS

www.mil-embedded.com

Figure 1 | Assuming it can identify the signal, the aircraft – or an adjacent one in this case – would correspondingly select an appropriate countermeasure signal to jam it. Image courtesy Keysight/NASA/USGS.

combination of measurement hardware and software, which can accelerate the data collection and make the analysis more manageable.

Applications such as radar target simulation and emulation require complex signals with frequency shift, delay, and channel effects. These signals have typically been generated and analyzed with digital signal processing engines or recorded to and played back from a deep-memory storage device such as a RAID [redundant array of independent disks]. One such block diagram of compatible instruments, including digitizer, arbitrary waveform generator (AWG), digital signal processor (DSP), and storage modules is shown in Figure 2.

The digital processing engines in conventional radar and EW systems are often implemented with field-programmable gate array (FPGA)-based system-level architectures. These FPGA-centric systems implement digital RF memory (DRFM) and other EW techniques in firmware via VHDL and Verilog. They are sufficient for intercepting and analyzing known waveforms on their pulse descriptor word (PDW) list. Unfortunately, www.mil-embedded.com

Figure 2 | Block diagram shows instruments used in radar target simulation and emulation.

the engines can lack the dynamic flexibility needed when encountering new waveforms generated on the fly by near-peer adversaries.

Future EW systems will need to be built with new devices and technologies to counter these unknown threats from the software-defined digitally programmable adaptive radars that are emerging. By deploying a heterogeneous architecture based on a highspeed processing engine working in conjunction with a partially reconfigurable FPGA, the system can synthesize a mix of responses to quickly create the best defense against the new unknown threat.

Partial reconfiguration offers modification of FPGA While FPGA technology offers on-site programming and reprogramming, partial reconfiguration (PR) takes this flexibility one step further. PR allows the modification of an operating FPGA design by loading a partial configuration file into reconfigurable regions of the FPGA. It does so without compromising the integrity of the applications running on those parts of the device that are not being reconfigured. This change of

MILITARY EMBEDDED SYSTEMS

July/August 2020 37

INDUSTRY SPOTLIGHT

Leveraging Big Data for Military Applications

the FPGA image without rebooting has enabled dynamically reconfigurable instruments and could be deployed in operational systems as well.

PR is also useful in those situations in which an interface is required to persist while the functionality changes. For example, when a FPGA system is interfaced with a host computer via PCI Express (PCIe) a full reprogramming of the FPGA breaks the communication link. PR, in contrast, enables the link to be maintained by keeping the interface circuitry active while the accelerator portion undergoes reconfiguration.

High-speed communication links are essential between these processors plus storage and other devices to enable quick responses to the unknown signals and also to manage the enormous amount of data. The Optical Data Interface (ODI) is a new point-to-point interface standard for instrumentation and embedded systems. ODI

The ODI standard specifies an MPO/ MTP multifiber push-on optical connector, which may be placed anywhere on a device. ODI works with any product format, whether AXIe, PXI, LXI, VPX, or a traditional bench instrument design. It works equally well with embedded systems, such as those found in military or aerospace applications, as it does with instrumentation. Through the standardized ports, ODI enables high-speed communications between instruments, processors, storage, and embedded devices in various form-factor combinations when configuring hybrid systems and solutions. The ODI family of specifications is best described as three layers, with each of the layers working in concert to achieve a high degree of interoperability.

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38 July/August 2020

MILITARY EMBEDDED SYSTEMS

breaks speed and distance barriers by using optical communication between devices over a pluggable optical fiber.

With speeds as fast as 20 Gbytes/sec from a single optical port and as fast as 80 Gbytes/sec through port aggregation, ODI is designed to help address these challenging applications in highspeed data acquisition, data processing, and signal generation. By contrast, a PCIe Gen 3.0 by 8 lanes bus interface – commonly found between modules in a PXIe chassis – has a maximum data transfer rate below 8 Gbytes/sec.

elma.com

Layers at work First, ODI-1 defines the physical layer, which is how bits and bytes get from one device to another. It describes a method of transporting packets, without defining what those packets are. This physical layer itself consists of two layers, an optical layer and a protocol layer. The optical layer consists of 850 nm VCSELs [radar target simulation and emulation lasers] and 24 lanes of multimode fiber optics, 12 in each direction. A device that transmits data is called a producer, and a device that receives data is a consumer, while there are two line rates, 12.5 Gb/sec and 14.1 Gb/sec. Devices that operate at the higher speed must operate at the lower speed as well, enabling upward compatibility. An ODI port is capable of over 160 Gb/sec per direction based on multiplying 12 lanes www.mil-embedded.com

By cre­ating an emulated environment and enabling hardware simulations of realistic condi­tions, such a [test] system could validate that these algorithms will work when deployed in the field. by 14.1 Gb/sec. (This rate is usually simplified as 20 GBytes/sec.)

The protocol layer is based on Interlaken, a chip-to-chip interconnect standard common in data centers, conceived by Cortina Systems and Cisco Systems.

Interlaken is supported by the major FPGA suppliers and managed by the Interlaken Alliance. It can deliver packets of data over a large number of lanes at very high speeds. Interlaken doesn’t define the packets, only their boundaries as a block transfer; Interlaken manages the health and alignment of the 12 ODI lanes without interrupting the data transfer. It also enables flow control from a consumer to modulate the average speed from the producer.

Next, ODI-2 specifies the transport layer, which is where the packets transported

by Interlaken are defined: ODI employs a standard packet definition, leveraged from the VITA 49 family of standards (The VITA organization is well-known for its VME and VPX standards, deployed in many embedded military and aerospace applications). VITA-49, known as the VITA Radio Transport (VRT) specification, defines common packet formats and protocols for software-defined radios. The VRT specifications have low overhead, are very general in nature, and are applicable well beyond radio communication.

Standard VRT packets are used for block transfers of data sent between devices, with consecutive VRT packets creating a “stream” of contiguous data. These VRT streams provide much useful information that can be extracted by softwaredefined SIGINT systems when attempting www.mil-embedded.com

Figure 3 | Test system diagram: Scenarios, emulators, system under test.

to locate, identify, and monitor a wide range of unknown signals. ODI-2 also uses VRT packets to aggregate ports and achieve proportionally higher data rates. For example, a four-port system quadruples the data bandwidth to 640 Gb/sec, or 80 Gbytes/sec.

Specifically, ODI has adopted VITA-49.2 for its packet definition. Embedded in the mandatory packet prologue are Stream ID, time stamps, and Class ID that identifies the data formats. VITA-49.2 time stamps are particularly important for radar systems, which must capture reflected pulses during precise intervals of time relative to the outgoing radar pulse.

Finally, ODI-2.1 defines certain data formats and context packets optimized for highspeed data streaming and processing. ODI-2.1 mandates 8-bit and 16-bit real and complex data transfers, along with specific methods for loading the data into the packet’s data payload. Context packets are used to indicate metadata about the data stream. Parameters may include the sample rate, reference level, bandwidth, or RF and IF reference frequencies. By adopting evolving standards that are being deployed in data centers and in embedded systems themselves, ODI expands its applicability from test and measurement to actual operational systems as well.

There are many challenges to the design and implementation of future cognitive systems. For one, the test system block diagram shown here in Figure 3 would be extremely valuable in developing and evaluating cognitive electronic attack algorithms. By creating an emulated environment and enabling hardware simulations of realistic conditions, such a system could validate that these algorithms will work when deployed in the field. This test system could be used for mission planning and training purposes as well.

The realization of such a test system benefits from these same technology advances; employing them offers the opportunity to both tightly integrate the measurement and operational equipment and enable hardware-in-the-loop substitution.

In conclusion, the convergence of several technology advances – namely PR, ODI, and VRT – are enabling a new class of software-defined EW, radar, and SIGINT operational systems and companion measurement solutions with enhanced data-handling capabilities. MES Chris Miller is currently a strategic planner in Keysight’s Technology Organization in Santa Rosa, California. Forty years ago, he joined Hewlett-Packard Laboratories in Palo Alto. The intervening time at HP, Agilent, and Keysight has been spent equally working in central technology organizations and as an R&D manager in signal analysis and lightwave product divisions.

Keysight • www.keysight.com

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WHERE TECHNOLOGY EXPERTS GATHER

MARKET TRENDS, TECHNOLOGY UPDATES, INNOVATIVE PRODUCTS Military Embedded Systems focuses on embedded electronics – hardware and software – for military applications through technical coverage of all parts of the design process. The website, Resource Guide, e-mags, newsletters, and print editions provide insight on embedded tools and strategies such as software, hardware, systems, technology insertion, obsolescence management, and many other military-specific technical subjects.

Coverage includes the latest innovative products, technology, and market trends driving military embedded applications such as radar, sonar, unmanned system payloads, artificial intelligence, electronic warfare, C4ISR, avionics, imaging, and more. Each issue provides readers with the information they need to stay connected to the pulse of embedded technology in the military and aerospace industries. mil-embedded.com

ADVERTORIAL

Q

What are the biggest challenges the FACE and SOSA Consortia face in getting their initiatives adopted within the military technology community?

At AdaCore we have been principally involved with the FACE Consortium, so our response is specific to the FACE approach.

First we want to emphasize that the FACE Consortium has achieved an impressive goal: designing a software architecture and data model that facilitate reuse of components across multiple avionics systems. This ambitious objective has been met through a consensus-based process involving the various stakeholders. The FACE approach is mature and has the potential to see significant adoption by military avionics suppliers. But there are challenges in several areas.

• On the business side, contracts for computer-based systems have historically offered little incentive, for either the agency procuring the software or the company developing it, to focus on reusability. Designing for reuse would add cost to the initial effort but realize savings only on later projects. This issue can best be addressed by the procuring agency, by taking a longrange view and including FACE conformance as a requirement or important criterion. Another businessrelated issue is the cost of conformance certification; how to simplify the process and thereby encourage certification without reducing assurance that the FACE requirements are met.

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Q

FACE AND SOSA Q & A ROUNDTABLE

• On the technical side, how to adapt as language standards or new development methods evolve?

The FACE Consortium processes have been designed to meet this challenge (one example is support for Ada 2012 in an upcoming revision to the Technical Standard) so the issue in practice is whether and how to make the needed adaptation. A related opportunity to adopt relevant processes from other certification standards: tool qualification as defined in DO-178C could be used in conjunction with FACE conformance certification.

• On the marketing side, how does the Consortium create an awareness of the FACE approach and its benefits? The FACE Technical Standard is lengthy, and some of the software engineering topics might not be familiar to engineers whose expertise is in avionics.

A possible solution: Provide training materials like tutorials and videos that accurately present the FACE technical approach and shorten the learning curve for potential adopters of FACE technology.

While the FACE approach faces some challenges to widespread use, all of them are surmountable.

AdaCore • www.adacore.com

FACE AND SOSA Q & A ROUNDTABLE

Why is SOSA so important to the military end user, the prime contractors, and the embedded hardware and software providers?

The SOSA Consortium is influential to bring Military Customers (DoD) and Prime Contractors (Suppliers) to a collaborative platform where Armed Services voice their varying demands; and in doing so, come up with ubiquitous solutions that satisfy requirements of all Branches. In turn, the common solution provides the Prime Contractors with larger product volumes and business model stability.

The Mission of The Consortium is to:

Involvement in The Forum by the second and third-tier suppliers of Industry Standard hardware and software is crucial to their business strategy by providing insight into the needs of The Customer while offering an opportunity to influence the trajectory of the design to adoption and market advantage.

• Enable technology transition

• Reduce development time and cost • Reduce deployment cost and risk • Increase commonality and reuse • Reduce sustainment and modernization cost • Support capability evolution and mitigate obsolescence

• Facilitate interoperability • Isolate the effects of change.

Meritec • www.meritec.com

EXECUTIVE SPEAKOUT

ADVERTORIAL

A case for sealed, conduction-cooled 1U/2U rugged rackmount servers

By Chris A. Ciufo, Chief Technology Officer at General Micro Systems, Inc.

Silent, high MTBF, with a wide temperature range and low EMI, an industry-first brings sealed, exceptionally rugged conduction-cooled servers to high shock/ vibration environments.

The Department of Defense uses air-cooled, rackmount servers by the truckload and boatload – racks upon racks installed in buildings, command post tents, ships and submarines, in the back of MRAPs and Strykers, and flying in reconnaissance platforms.

While the requirements for a basic server are similar however used, the environments in which they are used vary greatly, from air-conditioned data centers or field command post tents with fairly predictable temperatures to an open door to a Coast Guard Jay Hawk helicopter with rotors beating the air in a snow squall in Dutch Harbor, AK. Moreover, ground, ship and airborne platforms must also withstand shock, vibration, salt, fog, humidity and liquids like blood, de-icing fluid or diesel fuel. However, a typical COTS air-cooled rackmount server installed in any of these brutal environments faces a hard and likely short life. As discussed in my article elsewhere in this issue, the solution is conduction cooling, which has been the preferred approach to all military high-performance embedded systems – with the exception of servers.

Conduction-cooled chassis boxes are ATR- or small form factor (SFF)-type hard mounted or installed in trays and are common in massively metal ground vehicles or avionics platforms like fighter jets and airborne pods, where “ram air” from flight provides the sidewall flow-through or impingement cooling. Flow-through cooling is also common in wide body platforms like C-17, E-3, EA-6B, P-8A and others where the cabin is humanfriendly and air-conditioned air is readily available. Both chassis types – with a cold plate (vehicles and ships) or sidewall flow-through – are environmentally sealed.

Conduction-Cooled Chassis: Air or Cold Plate These sealed airborne or armored vehicles chassis boxes are completely passively cooled and may radiate or convect some heat into the surrounding environment.

However, they primarily rely on conducting heat from the internal electronics to either the hollow sidewalls or to the chassis cold plate usually found on the bottom of the chassis. Rigidly mounted to the vehicle, heat is then transferred from the box to the mounting tray or vehicle, where it is conducted away due to the massive heat sink offered by the vehicle itself, or air is blown through the cold plate sidewalls and exhausted elsewhere. This kind of cooling is also quite common in UAVs and helicopters, where lightweight SFF conduction-cooled chassis are installed in pods, mastmounted sights or against the fuselage.

Hybrid Conduction-Cooled Servers General Micro Systems (GMS) has been providing conduction-cooled ATR, small form factor (SFF), and specialty chassis like those described above for nearly 40 years. Our sealed products have been passively cooled without fans or with sidewall/plenum flow-through cooling, and we’ve recently applied this thermal experience to 1U and 2U rackmount servers.

The benefits to servers include high reliability and MTBF; superior cooling of Intel’s latest Scalable Xeon® 24 core (>150W) embedded CPUs; sealed chassis with substantially reduced EMI; high shock and vibration tolerance; the ability to add 38999 milcircular connectors, and completely silent operation (without 10,000 RPM screaming fans). In addition, in a 2U conduction-cooled server, up to two 250W Nvidia V100

GMS TITAN-1U conduction-cooled server

GMS TITAN-2U conduction-cooled server

GPGPU co-processors can be conduction cooled – as proven in our deployed X422 “Lightning” GPGPU artificial intelligence (AI) deep learning system. Dual 8-drive encrypted SSD cartridges and up to 10 add-in cards in only 2U prove that these are no-compromise servers for exceptionally rugged applications.

GMS’ 1U and 2U conduction-cooled servers utilize internal conductioncooled heat sinks and cold plates as well as our patented RuggedCool™ hotspot thermal cooling and other patentpending thermal techniques never before applied to production-quality, rugged COTS rackmount servers. Our TITAN Series 1U and 2U conductioncooled rackmount servers rely on a central radiator air plenum through which air is blown (or evacuated). All the internal thermal structures move heat into the central radiator plenum, which gives up its heat to the flow-through air to be exhausted out the rear (typical) or front (custom). The rack or vehicle system provides the airflow, allowing the server to be mounted in any location or orientation, including standalone without a rack.

General Micro Systems, Inc. www.gms4sbc.com

ADVERTORIAL

EXECUTIVE SPEAKOUT

AI System Design for Rugged Military Environments

By Braden Cooper, Product Marketing Manager at One Stop Systems The increased demand for Artificial Intelligence systems in commercial and military applications requires datacenter speed at the edge. Advances in data processing through compute acceleration has led to a tug-of-war relationship between data collection and processing. While commercial applications scale data processing through cloud-based computing in datacenters, military applications cannot always utilize these facilitating environments, requiring more portable and ruggedized solutions. In many field applications, data collection, storage, and processing take place at the source of the data, regardless of the environmental conditions. These mission-critical scenarios require special design factors beyond the typical commercial datacenter.

In designing an HPC system for military AI applications, defining the environment is a critical first step. Modern military environments vary greatly in terms of both thermal and structural design factors. The same system may be required to operate reliably on the ground in arctic, tropical, or desert conditions and in the air at various altitudes. Once the target environments are understood, the critical design factors can be defined.

For thermal design, the temperature range must be considered along with the conditions of the air itself: salt content, humidity, altitude, etc. For environments with condensing humidity or salt content requirements, material selection and special coating processes such as conformal coating are required to deter material damage and degradation over time. For high altitude applications, air density must be factored into thermal design as the volumetric flow becomes less effective. The mission-critical nature and per-unit cost of the ruggedized HPC systems often means the thermal requirements must be proven through computational fluid dynamics (CFD) simulations and validated through testing in humidity and altitude test chambers without the benefit of multiple costly prototype iterations For structural design, military applications often require unique form factors beyond the standard datacenter design template.

For mobile military applications, it is important to consider how the unit will be mounted or installed within the vehicle, which will translate to how the forces are imparted to the system and ultimately the electronics therein. As the potential mobile applications vary from naval to ground to airborne, the operational and transportation vibration levels of the environment vary as well. Vibration requirements can be further complicated by natural resonances – often requiring the system in design to not exhibit any natural modes below 100Hz. Beyond vibration, designs must also take into consideration load requirements to ensure operator safety in the event of sudden stops or crashes.

To meet these complex structural design requirements, finite

element analysis (FEA) simulation demonstrates how the vibrational and load forces applied to the system through the mounting structure relate to the natural modes and effective stress applied to the critical components within the system.

The results need to be considered against both the enclosure design and the requirements of the sensitive electronics within the system.

By validating military ruggedized HPC systems through analysis, simulation, and lab testing, the unit can be reliably deployed to mission environments with low risk of environmental failure.

Effective, up-front analysis and simulation of thermal and structural environmental requirements also reduce costs associated with prototype testing iterations and spares stocking for highend HPC systems tailored to military applications.

One Stop Systems (OSS) incorporates thermal and structural analysis through simulation as key design tools to meet the wide variety of environmental demands of some of the industry leaders in military HPC applications. From data ingest through FPGAs, to high-speed NVMe storage, to data processing through GPU computing, OSS is a pioneer in AI on the Fly®, bringing the compute power of HPC to the unique environmental requirements of military AI applications.

One Stop Systems www.onestopsystems.com

Disclaimer: This article may contain forward-looking statements based on One Stop Systems’ current expectations and assumptions regarding the company’s business and the performance of its products, the economy and other future conditions and forecasts of future events, circumstances and results.

EDITOR’S CHOICE PRODUCTS INS/GPS inertial navigation systems designed for accurate positioning A line of inertial navigation systems (INS/GPS) from Gladiator Technologies combines a 72-channel GNSS receiver and low-noise MEMS inertial sensors with an advanced Extended Kalman Filter (EKF) for accurate positioning during GPS outages. The LandMark60 INS/GPS – a high-performance, low-noise system – features 72-channel GNSS, RTK, and VELOX high-speed processing. The EKF enables error correction and continuous output during GPS-denied outages – within 3 nautical miles per hour/free inertial. This INS/GPS is designed to be highly durable and to withstand environmental vibration, shock, and EMI typically associated with commercial aerospace requirements. The LandMark60 in photo is aimed at use in flight control, navigation, stabilization, pointing, general aviation, and automotive testing.

These systems are designed to be highly durable and to withstand the types of environmental vibration, shock, and EMI typically associated with commercial aerospace requirements. The small LandMark005 INS/GPS is intended for use in unmanned aerial system (UAS) flight control, navigation, stabilization, and pointing in size-restricted applications that call for precision inertial performance.

Gladiator Technologies | www.gladiatortechnologies.com

KD-5600 family of digital differential measuring systems designed for range of applications Users in the small satellite, semiconductors, military/aerospace, high-precision metalworking, and UAS sectors are the target for the KD-5600 system’s host of features. Designed for noncontact linear position displacement sensing applications, Kaman released three configurations for tailored use: The KD-5656 (digital system), KD-5640 (analog system), and KD-5690 (FE system, photo left) are equipped with custom sensors, signal processing, analog-to-digital converter, and a custom calibration system to ensure precision and accuracy. For optimum operation for each channel, the KD-5600 system has two matched sensors. Input signals are filtered and size, weight, power, and cost (SWaP-C)-optimized for optimum operation, lower common mode noise, and drive signal. They also provide digital filtering as part of the signal conditioning to reduce signal noise.

The suite of products is designed with high resolution, bandwidth, and linearity and come with a serial peripheral interface bus for fast data transfers and no need for firmware. Additionally, the KD-5600 system samples data at eight times the standard data rate; oversampling at high volume provides higher resolution at the defined data rate, which results in signal resolution eight times better than a system sampling at the Nyquist rate. Using a 9D connector for reading data, power, and control signals, the system operates from a single power supply with a voltage range of between 8 and 28 volts.

Kaman Sensors | www.kamansensors.com

SPH Engineering offers bathymetric UAS solution SPH Engineering announced the launch of a new product to make bathymetric surveys of inland and coastal water. According to the company, a UAS integrated with an Echo Sounder is time- and cost-efficient and suitable for mapping, measuring, and inspecting tasks as well as environmental monitoring. A UAS equipped with an Echo Sounder enables the user to collect data with high accuracy quickly due to easy transportation and fast deployment and it is two times more cost-efficient compared to the traditional methods. It is able to operate in hard-toreach locations, unsafe areas, or hazardous environments. Locations not reachable by foot or dangerous for a human (steep coasts, mining pits, contaminated waters, terrain obstacles, etc.) as well as waters of ponds, lakes, and canals can be reached by a UAS. The integrated UAS system for bathymetry consists of an integrated with Echo Sounder or Ground Penetrating Radar (GPR).

The full integration is ensured by adding the onboard computer UgCS SkyHub to the system. Adding a laser/radar altimeter to the system enables the UAS to precisely follow the terrain, based on the data received from the altimeter. The vehicle’s flight is planned and managed using the full functionality of UgCS. Users may choose between a ready-to-use system or components like the UgCS SkyHub integration kit for self-assembling.

SPH Engineering | www.sph-engineering.com 44 July/August 2020

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EDITOR’S CHOICE PRODUCTS Software collaboration simplifies verification and certification of multicore avionics applications DDC-I and Rapita Systems announced the integration of Rapita’s verification tools (RVS) with DDC-I’s Deos DO-178C DAL A certifiable safety-critical real-time operating system (RTOS). The integrated platform is designed to simplify multicore verification and certification by providing the safety-critical timing information needed to satisfy CAST-32A guidance. The companies also intend the product to enable developers to simulate multicore resource contention, characterize interference patterns, and provide the certification evidence needed to prove that competition for shared resources does not adversely affect the execution of safety-critical tasks.

The hardware-agnostic integration of the companies’ products are portable to every architecture supported by Deos (PowerPC, Arm, and x86). Tracing is accomplished by applying RVS instrumentation with a trace mechanism available within the Deos kernel. Rapita’s RapiDaemons can be used to generate contention for specific resources that are shared by multiple cores in the system and then observe the resulting interference.

Together, these capabilities are intended to enable developers to understand timing and cross-core interference on Deos-based multicore systems and determine how to best coordinate multicore applications for optimal system performance consistent with the CAST-32A objectives.

DDC-I | www.ddci.com

Rad-hard mixed-signal microcontroller is space-qualified VORAGO Technologies has introduced a rad-hard mixed-signal microcontroller system-in-package (SIP) microcontroller with analog-to-digital converter (ADC) and ferroelectric RAM (FRAM) it has dubbed the VA10835. The part is space-qualified to the requirements of MIL-PRF-38534 class K. The MCU-based SIP uses a 32-bit Arm Cortex-M0 processor and includes a 16-channel/14-bit ADC. The microcontroller features a wide temperature profile of -55 °C to +125 °C. Additional memory features include 128 KB SRAM program memory, 32 KB SRAM data memory, 256 KB FRAM memory, and 1 KB eFuse memory (for unique ID).

The VA10835 is a SIP device that combines a 32-bit Arm Cortex-M0 rad-hard microcontroller, 16-channel 14-bit rad-hard ADC, and 256 KB rad-hard FRAM NVM in a single ceramic 68-pin QFP package with additional discrete components. The devices are connected internally using a four-layer ceramic substrate.

Vorago has aimed the SIP device at users who want to miniaturize the functionality into the smallest possible form factor.

VORAGO Technologies | www.voragotech.com

Rugged video encoders designed for multiplatform applications The Model 7840R 4-channel H.265 video encoder is an HD/SD part from Delta Digital Video that compresses video and audio signals, multiplexing them with metadata and other system information for real-time video transmission applications. Intended for end uses including ISR [intelligence, surveillance, and reconnaissance], the 7840R is capable of simultaneously encoding four channels of video with resolutions up to 1080p. Using the H.265 (HEVC) video-compression algorithm, the encoder provides high-quality video transmission at various resolutions and a wide range of bandwidths. The H.265 compression algorithm takes advantage of highly bit-efficient coding to provide encoded streams at nearly half the bandwidth of its H.264 (AVC) predecessor.

The unit is built on an advanced, low-power multimedia architecture that provides the horsepower for the computationally intensive H.265 algorithm, providing bandwidth efficiency for multichannel applications. This increased efficiency enables more channels to be transmitted over a given bandwidth, better-quality video for constrained bandwidth applications, or lower-bandwidth operation to extend the limits of ISR operation and reduce storage size requirements. The 7840R also provides an H.264 mode to support legacy infrastructures while providing a future growth path to H.265. Designed for any rugged airborne, ground mobile, or shipboard application, the video encoder is compliant with the full-motion video standards developed by the U.S. government’s Motion Imagery Standards Board (MISB).

Delta Digital Video | www.deltadigitalvideo.com www.mil-embedded.com

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July/August 2020 45

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By Editorial Staff

GIVING BACK | PODCAST | WHITE PAPER | BLOG | VIDEO | SOCIAL MEDIA | WEBCAST

GIVING BACK

Vets in Tech (ViT) Each issue, the editorial staff of Military Embedded Systems will highlight a different charitable organization that benefits the military, veterans, and their families. We are honored to cover the technology that protects those who protect us every day. To back that up, our parent company – OpenSystems Media – will make a donation to every group we showcase on this page.

This issue we are highlighting Vets in Tech (ViT), a national nonprofit organization that was founded to support veterans and returning troops by providing reintegration services where needed and connecting these recent and seasoned veterans – plus their spouses – to the U.S. national technology ecosystem. ViT’s stated purpose, according to information from the organization, is to bring together a tech-specific network, resources, and programs for veterans interested in what it terms the 3Es: Education, Entrepreneurship, and Employment.

The education component of the organization is focused on informing and training veterans about tech careers in programming plus design, law, business, marketing, finance, and other tech-related fields. The entrepreneurship segment aims to equip veteran would-be entrepreneurs and their spouses with mentorship and resources to build high-growth technology companies with such programs as monthly immersive meetups, which concentrate on such areas as product development, legal, growth, and investment strategies. The employment element of ViT offers veterans and spouses help with resume writing and interviewing, connects them with mentors in the tech world, provides job-matching services and job fairs in tandem with local tech companies, and works with corporate talent representatives and recruiters who aid Vets in Tech candidates with hiring and onboarding.

Founded in 2012 by Katherine Webster – a former executive at TechCentralSF and Sun Microsystems – ViT has grown to 12 veteranled chapters across the U.S., garnered hiring support from approximately 20 of the top technology companies in the U.S., and developed training programs with tech ecosystems across the country.

For additional information on Vets in Tech, please visit https://vetsintech.co/.

WEBCAST

PODCAST

Reducing SWaP in Vetronics Applications: How CMOSS Enables SOSA

End of Moore’s Law, small sats, custom microelectronics

Sponsored by Curtiss-Wright and Milpower Source

Small satellites and their reduced size, weight, power, and cost (SWaP-C) requirements are challenging microelectronics suppliers to deliver the performance of commercial technology while also maintaining reliability.

The Army’s C4ISR/Electronic Warfare Modular Open Suite of Standards (CMOSS) initiative, launched by the Army Combat Capabilities Development Command (CCDC) C5ISR Center (formerly CERDEC), is a modular open systems approach (MOSA) that essentially integrates multiple capabilities into one box for military vehicle electronics (vetronics) systems, that before each had a separate box. The initiative reduces size, weight, and power (SWaP) as well as long-term costs via open architecture and open standards.

In this podcast, editorial director John McHale discusses these challenges with Tom Smelker, vice president and general manager for Mercury Systems Custom Microelectronic Solutions in Phoenix, Arizona. They also also cover sensor processing trends, the ways in which artificial intelligence will affect future space applications, and what Smelker calls the “end of Moore’s Law” and its potential impact on the military electronics market.

This webcast will cover how CMOSS and SOSA harmonize together to reduce SWaP and enable commonality in hardware and software components for military vehicle systems.

This podcast is sponsored by Aerospace Tech Week, which will now take place on March 24-26, 2021, in Toulouse, France, after being postponed due to the COVID-19 pandemic. To learn more about Aerospace Tech Week 2021, visit www.aerospacetechweek.com.

Watch the webcast: https://bit.ly/2CfIDrW

Listen to the podcast: https://bit.ly/2WiJKyd

Watch more webcasts: https://militaryembedded.com/webcasts

Listen to more podcasts: https://militaryembedded.com/podcasts

46 July/August 2020

MILITARY EMBEDDED SYSTEMS

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