Autonomous & Connected Vehicle Handbook 2022

Planning for vehicle dynamics with simulation Page 6

AUGUST 2022

Keeping autonomous vehicles on track Page 8

The basics of dielectric resonator antennas Page 30

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES

next ev anxiety: cold weather if

you wandered around the Society of

Automotive Engineers’ annual trade show

earlier this year, you would have seen a number of ideas aimed at cutting power consumption in electric vehicles. One development in that category was from a company called BetterFrost.

It devised a more energy efficient windshield defroster. Instead of blasting the windshield with hot air, BetterFrost sends 200-to-400-V pulses about a microsecond long to windshields containing a silver-oxide or fluorine-tin-oxide layer that ordinarily blocks the sun to help keep car interiors cool. The pulses generate enough heat to melt the thin layer of frost directly touching the windshield so windshield wipers can break up and remove the rest. Because it only consumes about 5% of the energy old methods required, the new process is said to give a typical EV about 12 miles more range.

If you hang around online forums for EV owners or own one yourself, you’ll understand why developments like that from BetterFrost will probably find eager buyers. Online EV forums typically host a lot of bellyaching about the lousy range and charging problems that go with cold weather. On a forum for owners of Jaguar I-Pace electric SUVs, for example, one owner discovered he only had a range of about 90 miles in cold weather though the SUV’s advertised range is 292 miles. He also fumed about his level-one charger (a charger powered from 120 Vac). It couldn’t provide enough juice in cold weather to even pre-warm the passenger compartment, let alone charge the EV battery. Other I-Pace owners chimed in to advise keeping average daily travels to under 30 miles in the winter if a level-one charger was all he had.

I’d be willing to bet the car dealer didn’t bring up these details in the showroom. But that EV owner shouldn’t have been too surprised with

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his cold weather problems. Testing by the U.S. Dept. of Energy has revealed that cold weather reduces EV range by an average of about 41%.

About two-thirds of the extra energy consumed goes to heat the cabin. Of course, fuel economy drops for ordinary vehicles in cold weather as well, but not as much as for EVs. Fuel economy tests show that a conventional car’s gas mileage is roughly 15% lower at 20°F than at 77°F in city driving. It can drop by as much as 24% for short (three to four-mile) trips.

One reason EVs don’t do well as the temperature drops is that the battery electrolyte fluid becomes more sluggish. This slows down charging and reduces capacity. Additionally, to protect the battery, the EV onboard computer may limit how it’s used in extreme low temperatures.

One reason: Fast charging can damage the battery when the thermometer is low. EV owner literature usually mentions such drawbacks but tends not to express them in graphic terms.

The Tesla Model S owners manual, for example, advises: “In cold weather, some of the stored energy in the battery may not be available on your drive because the battery is too cold.”

Solid-state batteries now on the drawing boards will do away with liquid electrolyte and thus handle cold weather much more adeptly.

But despite rosy predictions from a few battery start-ups, these improved cells are probably 10 years away. To tide over EV owners until their debut, the Dept. of Energy offers ideas on its web site about how to improve EV range in the cold. One of these suggestions is to park your car in a warmer place. We’d suggest Miami.

leland teschler • executive editor

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Advanced Magnetics for ADAS

From high-current, high-efficiency power inductors to filter components for a variety of communications buses, Coilcraft has the magnetics for all of your Advanced Driver Assistance Systems Coilcraft offers a wide range of AEC-Q200 qualified products engineered for the latest advanced driver assistance systems, including high-temperature, high power density power inductors for radar, camera and LiDAR applications.

Our compact, low-profile WA8351-AL ultrasonic sensor transformer offers excellent temperature stability up to 125°C and

high performance for time-of-flight (TOF) sensing.

Also choose from our broad selection of common mode chokes and filter elements for a variety of communications buses.

To learn more about our advanced solutions for ADAS and other automotive/ high-temp applications, visit us at www.coilcraft.com/AEC. ®

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contents AU TO N O M O U S & C O N N E CT E D V E H I C L E S H A N D B O O K • AU G U ST 2 0 2 2

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bootloaders for arm cortex-a35/a5x mpus it pays to know the benefits of bootloaders for the arm cortex mpus which have long formed one of the backbones for embedded automotive applications.

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keeping hackers out of gps receivers resilient gps/gnss receivers protect inertial navigation systems from jamming and spoofing.

design tips for high-voltage protection in evs and hybrids the primary goal of ev protective circuits: keep vehicle occupants safe day-to-day and first- responders safe if the worst happens.

30

improved estimation of automotive radar signal strength the signal strength of automotive radar can be estimated from the target radar cross section and distance.

the basics of dielectric resonator antennas the mmwave equipment on connected vehicles is likely to sport dielectric resonator antennas that don’t look anything like conventional antennas.

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hybrid sensors for connected vehicles the dependence of smart vehicle features on sensing technology has manufacturers thinking about how to field devices that combine functions in economical ways.

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next ev anxiety: cold weather

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planning for vehicle dynamics with simulation vehicle dynamics play an important role in validating intelligent systems.

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keeping autonomous vehicles on track what av developers need to know about inertial navigation systems.

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designing-in “safe” rf levels new ics sense human proximity to keep the rf output of consumer devices within safe levels.

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evolving radar technology in adas even lidar may become unnecessary thanks to advances in highly integrated rf chips.

EE Classroom on Silicon Carbide

Silicon Carbide (SiC) has made its mark in bringing faster, a smaller, and more reliable components than its fellow semiconductors to market. While SiC components have been around for a couple of decades, there is still a lot to learn and a lot to consider when choosing the most suitable WBG semiconductor for your device. LET US HELP with tutorials, from looking at how WBG semis stack up in power conversion efficiency to an overview of SiC FETs and MOSFETs.

Check out our EE Classroom to learn more: www.eeworldonline.com/silicon-carbide-classroom

AU TO N O M O U S & C O N N E CT E D V E H I C L ES

planning for vehicle dynamics with simulation vehicle dynamics play an important role in validating intelligent systems.

michael peperhowe, dspace gmbh

a braking test scenario for a semi-trailer truck approaching an obstacle, in this case a bus. depending on the road surface qualities, the truck can leave its lane or jack-knife.

advanced

driver assistance systems and autonomous driving (ADAS/AD)

functions are designed to make everyone on the road more safe. Design engineers have long validated these functions by simulating them in test senarios involving other vehicles, pedestrians, and obstacles. But it is increasingly understood that the dynamic behavior of the vehicle itself plays an huge role in the operation of safety functions.

Physically, vehicles are more than a point mass, and their dynamic driving behavior has a particular influence on critical driving situations.

Consider a simple example of braking on surfaces with different friction coefficients: The vehicle starts skidding as torque is generated around its vertical axis. Even if stability systems intervene to prevent rotation, safety aspects must always be evaluated from the perspective of data coming in from sensors. But a question to ask is how dynamic driving effects influence the sensor output and imaging sensor output in particular. And how do functions for ADAS/AD (advanced driver assistance systems/ autonomous driving) use this information?

You don’t have to perform any elaborate and dangerous maneuvers on the proving grounds to investigate the vehicle’s dynamic behavior. With just a few clicks, simulations deliver revealing insights. To illustrate, we will look at selected relevant situations using the dSPACE tool suite Automotive Simulation Models (ASM) combined with the sensor-realistic simulation software Aurelion.

emergency braking at the limit

A semi tractor-trailor truck serves as a test vehicle for emergency braking at the limit on roads having different friction coefficients. The different friction coefficients might arise due to leaves, rain, snow, and so forth.

The electronic brake system (EBS) is switched off to highlight how

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vehicle dynamics influences the overall system behavior.

As the truck approaches an obstacle, the braking process is triggered by the automatic emergency braking (AEB) system, a part of an ADAS, based on its assessment of collision risk.

Two insights emerge from this simulation: First, with full braking at an ideal friction value, the truck stops completely well before the stationary obstacle. The truck and trailer remain in their own lane.

Second, with full braking with a lower coefficient of friction, a much more critical situation arises. The lower coefficient of friction lengthens the braking distance and completely changes the movement of the trucktrailer combination. The truck protrudes into the oncoming lane.

The examples show that simulation can realistically represent emergency braking only if all physical aspects of driving are taken into account (in this case friction values and jack-knifing between the truck and trailer). And the function of the ADAS can only be fully evaluated and validated by considering the effects of vehicle dynamics. The stability of the overall system must not be disregarded, especially when deciding on emergency braking at the limits of vehicle dynamics.

In addition, the ASM vehicle models also take into account how

during hard braking, the pitch angle changes the view of the detected obstacle for a camera mounted in the cab of a tractor-trailer truck. a strong pitch angle even leads to the obstacle only being partially within the FoV of the sensor, which results in a more difficult object detection (perception).

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S I M U L AT I O N

the braking system, both hydraulic and pneumatic, behaves. Thus these models offer the possibility of testing an ADAS/ AD ECU in conjunction with other ECUs to assess, for example, how ECUs intereact with an electronic stability controller (ESC). The benefit: The evalutation and validation covers the performance of the entire system, not just a single component. This system view gives ADAS/AD developers more options for understanding and adjusting the system behavior at an early stage.

pitch angle

When a tractor trailor truck brakes, the accelerations in the direction of travel cause the driver cabin to pitch toward the chassis.

This forces the camera sensors installed in the driver cabin to change their angle of view. The installed ADAS/AD control units compensate for this change in view so the distance to the detected obstacle is calculated correctly.

The pitch angle compensation must as well be part of the simulation. Compensation is essential for both object detection by individual sensors and for downstream sensor fusion. For example, a camera sensor installed in the cabin must see an obstacle in the same position as the radar sensor installed at the bottom of the chassis. Otherwise, there is a risk the entire system could fail, with potentially serious consequences.

Depending on the situation, a detected obstacle can disappear partially or even completely from the sensor’s field of view (FoV), especially in the presense of strong braking decelerations and the resulting high pitch angle. The behavior of the ADAS/AD in these particularly critical situations must be known and validated.

This physical behavior can be clearly displayed with ASM Truck and correctly integrated into the simulation. The physicsbased sensor models in Aurelion let you freely configure the sensor position as, for example, the location of the camera sensor in the cabin with additional degrees of freedom.

One important function of ADAS/AD control units for semi trucks is active lane keeping assistants (LKA). They must not only detect the road correctly but also function properly despite external disturbances. Such disturbances can arise, for example, when the vehicle is in a rut or lane groove and must eeworldonline.com

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counter steer. For reliable validation of the LKA system, it is therefore necessary to be able to realistically represent such disturbance variables in a closed-loop simulation.

With the ASM Road simulation model, any road surface can be simulated and flexibly parameterized. This gives you very broad test coverage with reproducible tests that are impractical in real test drives.

Another aspect that is particularly important for trucks is the effect of crosswinds on automated lane keeping. High lateral wind gusts can impinge on trucks as they pass obstacles and other semi tractor trailers. The gusts can push hard enough on vehicles with trailers and semi-trailers to cause instabilities.

The ADAS/AD control unit must recognize these and respond appropriately.

Again, ASM simulation can replicate a wide variety of such situations. This allows designers to create algorithms having a high level of maturity at an early stage. Last but not least, these tests are essential for validating the control units.

The inclusion of highly accurate vehicle dynamic system behavior makes it possible to simulate the influence of physical effects on ADAS/AD systems and to use them productively for validation. In this way, vehicle dynamics simulation makes an essential contribution to reliable development and validation and ensures that ADAS/AD ECUs are robust.

When there are fatal consequences during critical driving situations, the cause can often be traced back to the interaction of different effects. The precise combination of these effects often cannot be duplicated on a test track, but are possible in the simulation.

Realistic traffic and vehicle dynamics simulations provide a foundation for the efficient development of ADAS/AD systems.

Simulations improve both test depth and test breadth which, in turn, boost the quality of the individual safety functions and the way they interact with the overall system.

references dspace gmbh, www.dspace.com

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with the asm road simulation model, any road surface can be simulated and flexibly parameterized. the result is a broad test coverage that can’t be duplicated in real test drives.

a crosswind simulation as might arise when a tractor-trailer truck passes a bus.

disclaimer note: all simulations shown were performed with the dspace multi-physics tool suite asm (automotive simulation models). the sensor simulations and animations were calculated and rendered using the high-fidelity 3-d software aurelion.

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keeping autonomous vehicles on track

what av developers need to know about inertial navigation systems. james fennelly, acienna inertial measurement systems

combining imu and wheel-speed sensor data with precision location correction, the inertial navigation system is an integral part of the sensor suite needed for the safe navigation of autonomous vehicles.

the

inertial navigation system (INS) is essential to autonomous

vehicles. It provides timing information for sensor synchronization and rapid updates of velocity, position, and attitude needed for the ADAS (advanced driver assistance systems). It complements perception sensors for localization.

For highly accurate localization with high availability, the INS must contain a dualfrequency Global Navigation Satellite System (GNSS) receiver with real-time kinematic (RTK) abilities and a high-performance inertial management unit (IMU). Integrity monitoring in the INS—where the navigation system detects faulty measurement sources before they corrupt the outputs--is also crucial for automotive applications. In extreme cases when the environmental adversity causes the perception sensor and the GNSS receiver to fail intermittently or permanently, the ADAS can continue to work based on dead reckoning thanks to the self-contained nature of the IMU.

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“w here am i?”

The answer to this question is critical for the successful, safe operation of self-driving vehicles. How does the autonomous vehicle accurately know where it is? The answer is the INS. An INS system is typically composed of a GNSS receiver, an IMU, and some pretty advanced algorithms.

The INS uses standard positioning techniques to generate location with an accuracy of a few meters. For autonomous driving applications that require lane-level accuracy, additional carrier-based positioning techniques, such as RTK, are required for centimeter-level accuracy.

For instance, say the vehicle is approaching a fork on the highway. The lane usually widens. Having centimeter-level accuracy can help autonomous vehicles better execute the sharp steering motion and make for a safer and smoother exit from the highway.

An IMU is often composed of two sets of sensors – three gyroscopes and three accelerometers. The gyroscope measures the angular rate of three orthogonal axes.

Integrating the angular rate along the three axes over time generates roll, pitch, and yaw values which define the attitude of an

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object. Similarly, the accelerometer measures linear acceleration in three orthogonal axes.

Integrating acceleration over time provides velocity, and integrating velocity over time yields distance traveled. An IMU with gyroscopic and accelerometer sensors can provide measurement over six degrees of freedom (6-DOF).

an imu uses its accelerometer and gyroscope to capture measurements over six degrees of freedom – three axes of movement (forward and backward, left and right, and up and down) and three axes of rotation (roll, pitch and yaw).

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VEHICLE POSITIONING

unlike perception sensors and gnss signals from satellites, imu sensors are immune from harsh environmental conditions and physical obstructions like tunnels and foliage. why imus may include a magnetometer

An accelerometer can also be used to calculate roll and pitch values with respect to earth’s gravitational force and correct gyroscope drift.

However, accelerometers cannot be used to detect yaw because the change of yaw is orthogonal to the gravity vector. With regard to the earth’s magnetic field, the magnetometer measures the magnetic field strength in three dimensions. It can help to determine heading

When the GNSS signals are blocked by a tunnel, a covered parking lot, tall city buildings or even heavy foliage, the INS can use the IMU measurements to continue to compute positions, velocities, and attitude. This technique is called dead reckoning. When GNSS conditions are good, the GNSS receiver generates continuous positions and velocities which are used to constrain the INS estimates.

When GNSS conditions become poor, the INS continues to output positions, velocities, and attitude based on dead reckoning for ADAS-enabled navigation.

For L2+ autonomous driving, the autonomous vehicle must know the surroundings in order to navigate. It needs to be equipped with perception sensors and/or HD maps to gauge the traffic, what is ahead of the vehicle and beside the vehicle, the speed limit, and so forth. The INS can provide precise position, velocity, acceleration, attitude, and time. Unlike with the perception sensors, IMU operation is independent of the environment.

If the perception sensor fails due to adverse environmental conditions—for

an example of an ins is the aceinna ins401 which includes on-board triple redundant imu and fusion algorithms. measure of the gyroscope drift over time.

Because the rate output of the gyroscope is integrated to calculate change in angles (roll, pitch, and yaw), any error associated with drifts causes accumulated error in relative angles.

Furthermore, these angular errors translate into position errors over time. For automotive applications where there could be GNSS blockages for minutes or longer, a high-performance IMU is necessary in the INS for

for next generation autonomous vehicles, there are three critical ins requirements: high accuracy, high availability, and high integrity.

(i.e., yaw) as well as roll and pitch of the object.

A magnetometer in the IMU can help with detection of the initial heading of an object and correct integration errors of the yaw gyroscope in the sensor fusion algorithm.

In ACEINNA’s inertial products, such as RTK330LA, three IMUs are used to construct a triple-redundant sensor architecture. With ACEINNA’s proprietary fusion algorithm, the system only uses valid IMU measurements. Any defective sensor output or errant dataset can be ignored or down-graded in importance. eeworldonline.com

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example snow, rain, or dust—the IMU can continue generating rotation and acceleration measurements so the INS can operate. To maintain ADAS features such as lane keeping, lane centering or hands-off on highway, the INS is fundamentally needed because it provides absolute positioning and redundancy in the vehicle. The INS is also used to precisely synchronize and stabilize perception sensors in an autonomous driving system.

Bias instability is one of the performance parameters of the gyroscope. It is a direct 8 • 2022

high accuracy positioning.

For GNSS receivers, the key to high-accuracy positioning is the ability to resolve errors in distance and time from the satellites to the receiver antenna. When the satellite signal travels through the atmosphere, the ionosphere can delay the signal reception. The ionospheric error is a major contributor of errors to achieving centimeter-level accuracy. The dispersive nature of the ionosphere results in an ionospheric delay that varies depending on the frequency of the signal. A GNSS receiver that can track dual frequencies, e.g., L1 and L2, can compare the delays of these two signals and correct for the ionospheric error.

Tracking signals from multiple constellations enables a GNSS receiver to DESIGN WORLD — EE NETWORK

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increase its availability. When obstructions block one signal, the receiver can utilize a signal from another constellation to stay online. If in a rare occasion a constellation fails, the GNSS receiver can still have access to the other constellations and ensure the availability of the solution.

The measurements provided by the IMU can include several error sources. When the INS is integrating the measurement samples, errors also accumulate. The INS needs an external reference to correct those errors and correct its position drift. The odometer is also an external reference.

It provides independent measurement of displacement and velocity of the vehicle to aid autonomous navigation and reduces errors.

The integrity of a system describes how trustworthy the autonomous guidance system is. The positioning accuracy is calculated in post-processing when comparing the unit-under-test to the reference (i.e., the true position). In real time, the accuracy of the INS is unknown and its trustworthiness uncertain. An integrity monitoring system will have a protection level and an alert-limit parameter. The protection level is a statistical bound error computed for each positioning system calculated and the alert limit is determined by the application.

When the protection level exceeds the alert limit, the integrity monitoring system will raise an alert and warn the user that the INS is either unavailable or possibly generating misleading information.

Integrity monitoring is critical for applications that could affect safety of life.

Another factor to consider is the operating and support costs. L2+ autonomous driving via perception sensors and HD maps would require cloud infrastructure and maintenance and a lot more processing power in real time. These measures would add significant cost to the autonomous driving system. Correction providers would also need to charge a fee for service subscriptions to maintain their infrastructure and expand their coverage.

Fortunately, technologies for MEMS INS are developing at a fast pace, keeping down INS costs. Critically, when used with other perception sensors (cameras,

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radar, lidar), precise positioning helps cars anticipate the next maneuver and increase the safety and quality of the ride. Precise positioning in autonomous vehicles can also improve the performance (safety, reliability etc.) of many ADAS functions such as lane centering, lane change assistance, and lane departure warning.

at the 2022 ces, aceinna announced its ins40x family for autonomous vehicle navigation.

It combines centimeter level precision accuracy, ease of integration, and high levels of availability, reliability and integrity, at a competitive price. the ins401 is the first product in the ins40x family, containing one main connector and one rf connector.

references aceinna, www.aceinna.com/ inertial-systems

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SECURITY

keeping hackers out of gps receivers resilient gps/gnss receivers protect inertial navigation systems from jamming and spoofing.

the

demand for accurate and affordable

navigation is on the rise thanks to the growth of automation and robotization. Of coxurse, the go-to technology for navigation is GPS—able to locate receiver position to within 16 ft or less—and other GNSSs: Russia’s Global Navigation Satellite System (Glonass), China’s BeiDou Navigation Satellite System, the European Union’s Galileo, Japan’s QZSS and India’s NavIC. Most autonomous navigation technologies include an inertial navigation system (INS), which consists of a GNSS receiver and an inertial measurement unit (IMU) sensor. The GNSS receiver provides absolute positioning in terms of geographic global coordinates while the IMU measures heading, pitch and roll angles which give orientation information about the system on the move.

While GNSS provides absolute positioning, the IMU

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measures relative movement, which is subject to cumulative error called drift and needs regular “recalibration.” In a GNSS/INS system both sensors are fused in such a way that the GNSS provides regular IMU “calibration” and the IMU provides angles and extrapolation or “smoothing” of GNSS. When selecting a GPS/GNSS positioning receiver it is crucial to understand the vulnerabilities of its sensors and how vulnerabilities could affect the navigation system.

For robots and autonomous devices, availability is key to ensuring continuous and reliable service. Safety also must be considered for robots and drones operating near people. GNSS jamming or spoofing must be detected and flagged immediately so other sensors can take over.

Jamming overpowers weak GNSS signals, causing accuracy degradation and possibly even loss of positioning. In a nutshell, jamming arises when a signal at the GNSS frequency is strong enough to overwhelm the GNSS receiver, preventing it from seeing the real GNSS satellite signal (which is

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maria simsky, septentrio

typically on the order of -125 dBm).

Unintentional jamming sources include radio amateurs, maritime and aeronautical radiolocation systems as well as electronic devices sitting close to the GNSS receiver. There are also intentional jamming devices; these “jammers” are sometimes found on vehicles trying to avoid road tolls.

Jamming results in loss of positioning so the GNSS receiver can no longer be used as part of the INS solution. Jamming can lead to longer INS initialization

times or a switch to dead-reckoning mode (IMU only), where position accuracy starts to drift. Jamming can also result in measurement outliers which impact both deep and tight-coupling GNSS/INS algorithms. (Briefly: In looselycoupled algorithms, the positions and velocities estimated by the GPS receiver are blended with the INS navigation data. In the tightly-coupled method, GPS raw measurements are processed through a unique Kalman filter with the measurements coming from

gnss/ins systems commonly check positioning for outlier readings to detect spoofing. however, if the spoofer uses small positioning increments, which are within thresholds of allowed drift, spoofing is much harder to detect.

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES when GNSS satellite transmissions are lost for longer periods. Spoofers can exploit this drift phenomenon to hijack positioning gradually, in increments comparable to the expected drift.

To combat spoofing, GNSS receivers must decipher spoofed signals from authentic signals. One telltale sign: Spoofed signals are often a lot stronger than ordinary satellite signals, so a large signal is suspicious. Once signals are flagged as spoofed, they can be excluded from positioning calculations.

Use of sensors other than GNSS, such as an IMU or odometry, can help flag spoofing by detecting inconsistencies between GNSS and the other sensors. While such sensors help reduce spoofing risks, they are insufficient to provide full protection because they only output relative positioning which also is subject to drift.

A common technique used by GNSS/INS systems to detect spoofing is to continuously check GNSS, IMU and odometry data for consistency. If the spoofing attack keeps positioning increments within the allowed thresholds, which are set to allow for drift, it would go undetected by such a mechanism.

That is why anti-spoofing resilience should be built into several system components on both GNSS and INS levels.

detecting spoofing the red line is a gnss/ins system with a common spoofing check which is “hijacked” by a spoofer that uses small positioning increments. the magnitude of these spoofed increments is small enough to be below the drift threshold of the imu, which makes it acceptable for the ins system shown by the red line. the orange line is a gnss/ins system which stays on track because the gnss receiver detects the spoofing. if the spoofing attack is limited to a few signals, the gnss receiver can avoid the attack by discarding the spoofed signals from its positioning solution. the inertial sensors to estimate the position, velocity, and time. The main advantage of the tight integration is the possibility to update the position in scenarios with poor signal quality or limited coverage.)

Spoofing is a real threat to GNSS-based INS systems. It is mitigated most effectively by incorporating security mechanisms into all system sub-components. However, because spoofing takes place on the level of the GNSS signal, the receiver can employ a number of sophisticated methods to detect and mitigate spoofing.

Basically, spoofing is an intelligent form of interference which makes the receiver believe it is at a false location. During a spoofing attack a radio transmitter located nearby sends fake GPS signals into the target receiver. In one

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spectacular spoofing experiment a Tesla car was “misled” to take an exit from a highway rather than following the highway as it was supposed to. Another example arose when Pokémon GO fans used inexpensive software-defined radios to spoof their GPS position and catch the elusive Pokémon without leaving their home.

There are two principal ways of spoofing. The first is dubbed meaconing.

It consists of intercepting, storing, and then rebroadcasting GNSS signals later on. The second consists of generating and transmitting modified satellite signals.

During a spoofing attack an INS could be “hijacked” if the spoofer uses small increments in positioning, which common anti-spoofing methods may not detect. For example, GNSS/ INS systems can have a drift of a meter or more

8 • 2022

When anti-spoofing is built into the GNSS receiver, the system rejects the spoofed signal and switches to dead-reckoning, which allows it to stay on the right track. If the spoofing attack is limited to a few signals, the GNSS receiver can avoid the attack by discarding these spoofed signals from its positioning calculations.

the best gnss/ins spoofing protection comes from resilience built into multiple system components. on the gnss receiver side, anti-spoofing security can be incorporated in hardware and software, which is the approach used in the septentrio aim+ technology.

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SECURITY An INS system will be more resilient if the GNSS receiver can indicate spoofing or, even better, if it can mitigate spoofing itself. Thus, it is important to understand what constitutes a strong internal anti-spoofing defense system or a warning system. One aspect of anti-spoofing is to provide lots of information about received GNSS signals, giving users insights into spoofed signals such as time stamps and power levels.

A GNSS receiver design which implements security measures will include spoofing resilience at various levels. For example, consider the Septentrio AIM+ Advanced Interference Mitigation technology. It is a jigsaw puzzle of various antijamming and anti-spoofing components built into receiver hardware as well as software: •

• •

Signal processing hardware includes OSNMA (Open Service Navigation Message Authentication), a data authentication function. Galileo is the first satellite system to use OSNMA antispoofing directly on its signal. This feature provides assurance that received Galileo navigation messages are authentic and have not been modified. Other security measures include signal comparison and anomaly detection, and satellite consistency check-in tracking—basically looking at signals from multiple satellites for consistency.

Measurement engine (software): quality checks of raw measurements Positioning engine (software): receiver autonomous integrity monitoring (RAIM+) and proprietary algorithms. RAIM+ cross-checks for individual measurements that disagree from the rest sufficiently to create a potential for unaccepted errors.

It requires measurements from a minimum of five satellites to detect a faulty measurement and at least six satellites to detect and exclude a faulty measurement.

Both the GNSS receiver as well as the INS have their own mechanisms for spoofing protection. But resilience comes from the combination of detection and mitigation mechanisms working together on component level.

As in any field affiliated with security, continuous improvement is a necessity for antispoofing and anti-jamming mechanisms. The concepts discussed in this article are valid not only for GNSS/INS systems but for any sensor fusion system, which includes a GNSS receiver. Smart GNSS technology protects receivers from jamming and spoofing at the core level, ensuring safe and reliable system operation.

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13

references septentrio, www.septentrio.com tesla model 3 spoofed off the highway – regulus navigation system hack causes car to turn on its own. https://www.regulus.com/blog/tesla-model-3-spoofed-off-thehighway-regulus-navigation-system-hack-causes-car-to-turn-on-its-own

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improved estimation of automotive radar signal strength

the signal strength of automotive radar can be estimated from the target radar cross section and distance.

sir

Robert Watson-Watt is generally credited as radar’s inventor, having developed the first practical system in 1935 and

later applying radar to aircraft and weather. We’ve since used radar to monitor everything from ballistic missiles to bird migration. Automotive radar is a recent technology which may provide safer driving, perhaps even autonomously. In that regard, recent improvements upon a historic radar signal strength formula allow it to be more generally applicable to automotive applications.

In nearly all nonautomotive contexts, a simple formula predicts the return signal strength: Pr/Pt = σ GrGtλ2/(4π)3R4

Eqn. (1)

where Pr and Pt are the received and transmitted power, W; σ is the target radar cross section (RCS); Gr and Gt are the receive and transmit antenna gains, unitless; λ is the wavelength, m; and R is the distance between radar and target, m. σ has units of area, but is usually reported in dBsm, decibels relative to 1 m2.

Intuitively, this classic radar signal formula is just the roundtrip (twoway) generalization of the famous Friis’ formula for one-way broadcast.

To see this, let us first note that RCS is not the physical projected area Aeff of the target object. Instead, for a perfectly reflecting object, the RCS is given by

σ = 4π Aeff2/λ2 = GobjAeff

Eqn. (2)

where we have used the relationship between antenna gain and area Gobj = 4π Aeff/λ2 between gain and area. Namely, we can think of the target object as a passive transponder that receives the incident radiation with an effective capture area Aeff and retransmits it with an (object) antenna gain Gobj. This makes perfect sense because RCS is defined as the (direction-dependent) equivalent isotropic scattered power divided by the incident planewave intensity.

It is well known that Friis’ formula is strictly valid only when the transmitter and receiver are mutually in each other’s far field.

Fraunhofer diffraction hasn’t fully developed at close distances, so the 1/R2 power-versus-distance dependence flattens out. Likewise, it is appreciated that Eqn. (1) is invalid when the target lies in the near field of the radar. Much less appreciated is the reciprocal (mutual) validity requirement that the radar must also lie in the far field of the target

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8 • 2022

greg lee, keysight technologies

object, but this logically follows from our consideration of the target as a transponder in the preceding paragraph.

Automotive radars, working in either the 24 or 76-81 GHz bands, detect targets at ranges up to ~300 m (in some cases up to ~1 km) and down to less than a meter. Engineers designing or using these sensors must be careful not to apply the classic radar formula Eqn. (1) unconditionally. As an example, consider a delivery truck whose rear is 2-m wide by 3-m high, so Aeff = 6 m2. λ = 3.9 mm at 77 GHz, so if the rear surface were a perfectly flat mirror, the RCS should be 75 dBsm. Reported 77 GHz RCSs for cars and trucks are 20-45 dBsm, implying considerable wide-angle scattering rather than retroreflection. For arguments sake, let us take 40 dBsm as the trucks RCS, Gr = Gt = 15 dB, and R = 0.5 m. Then Eqn. (1) predicts the radar receives 22% more power that it transmits, clearly impossible. If the truck’s rear had been a perfectly flat mirror, Eqn. (1) would have predicted 35 dB of roundtrip gain – the world’s energy problems would be solved!

What is wrong? The most obvious problem in the calculation is the truck is so close that most of its rear isn’t even illuminated by the radar.

For the stated radar antenna gains and distance, only about 1% of the truck’s rear lies within the radar’s field of view (FOV).

In the real driving world, there is also considerable signal strength variability. This variability arises from several factors including ground bounce, object orientation, and polarization effects. Ground bounce is the classic example of multipath propagation which can result in either a 6 dB increase or deep fading, depending on whether the direct and bounce paths constructively or destructively interfere with each other.

The interference versus range even has subtle polarization dependence.

Only spheres have orientation-independent RCS. Cars, trucks, bicycles, and pedestrians will all present different σs depending on what view they present the radar. Because the wavelength is so short at 77 GHz, even small changes in orientation can shift the effective retroreflecting zones in any of these classes of objects. This causes not only variation in signal strength, but also angular shifts of sub-object detections in the case of modern imaging radars.

Both the mean estimation error when misapplying Eqn. (1) and the signal strength variation can be appreciated by a simple experiment Keysight performed in an empty parking lot. A commercial 77-GHz automotive radar with a far field of about 1-2 meters was fixed in the parking lot; a car (Volkswagen Golf) was at first parked, then slowly driven away from the radar, then put in reverse and backed up, and finally re-parked. A nearby figure shows the reported range and RCS of the car as a function of recorded time.

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AU TO M OT I V E RA DA R the target object and of the radar itself as distance breakpoints, but it is better to employ differentiable functions. That is, a more realistic representation of the expected return signal strength, disregarding fluctuations for the moment, should feature the FraunhoferRayleigh far field distances as soft transitions.

Such a soft breakpoint formula presents itself in the theory of Gaussian beams. A nearby figure illustrates how diffraction is elegantly represented by the hyperbolic “blooming” of a Gaussian beam.

radar temporarily tracking a volkswagen golf driven in a parking lot: distance (top) and perceived rcs (below). each radar frame is about 66 ms.

First, notice the ±10 to ±20 dB fluctuations in the RCS. These arise from the factors noted above and perhaps others. Second, the mean perceived RCS is about 10 dBsm when the car is 60 m from the radar but drops to about -10 dBsm when it is 5-8 m away.

Of course, the car has neither shrunk nor donned cloaking material when it is closer to the radar. The radar software has simply misapplied Eqn. (1) to convert roundtrip received signal efficiency to RCS at distances where the radar is no longer in the far field of the car, leading to a perceived RCS that falls dramatically as distance shrinks. This dramatic falloff in reported RCS is problematic because it can lead to misclassification of objects – for example, the car might be reclassified as a pedestrian.

We now suggest a pragmatic improvement to Eqn. (1) suitable for automotive radar applications. What is needed is a formula (or formulas) which reduce to Eqn. (1) at large distances but capture the notion of incipient (rather than fully developed) diffraction at closer distances. We can think of the Fraunhofer or Rayleigh ranges of eeworldonline.com

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hyperbolic beam waist evolution of a Gaussian beam. The beam waist is the radius from the beam axis at which the intensity drops off by a factor e2 from the axial intensity (at the same range). dashed red lines are the asymptotes of the beam waist profile.

Due to conservation of total propagating power, intensity on the beam axis at any range is inversely proportional to the square of the beam waist (that is, beam diameter) at that range.

Because the beam-waist-vs.-range curve is a hyperbola, intensity varies with distance from the focal plane as 1/(R2+RR2), where RR is the beams Rayleigh range given essentially by the focal spot area divided by λ. (One can quibble about a factor of two, but it is beyond the scope of this article to discuss such matters.) For R >> RR, one recovers the usual 1/R2 dependence predicted by Friis, as seen from the linear waist growth vs. range at large R. Conversely, for R << RR one has nearly constant intensity since one is so near the focal plane that diffraction loss is minor – the waist remains nearly constant at these distances.

How should we generalize the simple, attractive Gaussian beam idea to radar? Two extreme situations of roundtrip propagation can constrain candidate approximate formulas.

The first ideal scenario is when the target object is a large retroreflecting mirror. The 8 • 2022

second is when the target is still a mirror but now is smaller than the radar itself.

In the first scenario, when the mirror object is close enough, a Gaussian beam emanating from the radar will bounce off the mirror and continue to diverge on its return path. For example, the radar receives a wave whose spatial profile is that of a Gaussian beam which has travelled 2R from its focal plane.

Based on this observation, a simple pragmatic formula for roundtrip signal strength is Pr/Pt = σ GrGtλ2/[(4π)3(R2+Ravg2)(R2+Robj2)]

Eqn. (3)

where Ravg is the arithmetic mean of the radar’s transmit and receive Rayleigh ranges, and Robj is the target object’s Rayleigh range. The appearance of Robj in Eqn. (3) is intuitive from our discussion above, but the appearance of Ravg may seem mysterious and so bears elaboration.

As we have emphasized, the radar and the target should mutually be in each other’s far fields 4 for the 1/R law to apply. Hence, the appearance of soft breakpoints associated with both radar and target should not surprise. However, one might naively expect that Ravg would be the geometric mean of the radar’s transmitter and receiver Rayleigh ranges, and yet Eqn. (3) features the arithmetic mean. Why so?

The geometric mean is always less than or equal to the arithmetic mean. For example, suppose the transmit Rayleigh range is zero but the receive Rayleigh range is two meters. The geometric mean vanishes but the arithmetic mean is one meter. If we were to bring the large, mirror-like object down to zero distance, using the geometric mean would predict Pr/ Pt = infinity, which is physically impossible.

Of course, this is the same problem with the classic Eqn. (1), only more so. On the other hand, a little elementary calculus (namely, Gaussian overlap integrals) shows that the arithmetic mean is the correct Rayleigh range to use for the folded Gaussian beam scenario.

In the second scenario where the target object is smaller than the radar, one can think of the target as spatially filtering the incident wave before retroreflecting it. In this case, the target is truly acting like a transponder, so the roundtrip efficiency should simply be a product of two one-way modified Friis factors. The equation we propose is Pr/Pt = σGrGtλ2/[(4π )3(R2+Rot2)(R2+Ror2)]

Eqn. (4)

Here Rot is the arithmetic mean of the transmitter and object Rayleigh ranges, while DESIGN WORLD — EE NETWORK

15

AU TO N O M O U S & C O N N E CT E D V E H I C L ES Ror is the arithmetic mean of the receiver and object Rayleigh ranges. Once again, the arithmetic means arise from Gaussian beam calculus. These mean Rayleigh ranges are what “modify” the one-way factors from being pure Friis-law factors.

Incidentally, when the object has the same Rayleigh range as the transmitter and receiver, Eqn. (4) becomes identical to Eqn. (3). This makes sense, because one should have a continuous transition from “small” to “large” objects.

smoothed uncorrected rcs data from figure 1 (blue); same data corrected using robj = 35 m, ravg = 0.65 m (red). ravg is our estimate for the radar used in the experiment, but since the car is never closer than 5 m, the red curve is insensitive to this estimate.

predicted roundtrip signal efficiencies for a car with aeff = 0.25 m2, λ = 20 dbsm, and gt = gr = 18 db. the cars aerodynamic shape explains its seemingly small aeff.

Nearby, we show a 77 GHz example of the roundtrip signal efficiency using Eqn. (3) and compare with the classic Eqn. (1). Note that whereas Eqn. (1) predicts unbounded increase of Pr/Pt as distance decreases, Eqns.

(3) and (4) predict signal strength saturation.

The latter is what one physically expects, whereas the former is unphysical, e.g., allowing perpetual motion machines, and is responsible for the drop in perceived RCS with diminishing distance which many automotive radars erroneously report. The latter equations lead to more constant perceived RCS, a highly desirable outcome because it aids in proper object classification, a notoriously difficult task in autonomous driving.

To substantiate this claim, we have smoothed the data from the right-hand portion of Figure 1 and replotted in Figure 4, first without correction and then with correction based on Eqn. (3). Since the product of the radar’s receive and transmit antenna gains happens in both Eqn. (1) and Eqn. (3), there is no need to know these gains in applying the “Rayleigh-based” correction.

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Furthermore, the estimated Rayleigh range(s) of the radar is(are) about an order of magnitude less than the minimum range of the car in the experiment, so the only parameter that really matters is the effective Rayleigh range of the car itself. Like many compact hatchbacks, the upper rear of a Volkswagen Golf is slanted, so one expects retroreflection mainly from the lower rear of the chassis and bumper. This suggests a normal-to-beam surface area of perhaps 0.2 m2, commensurate with our parameter choice Robj = 35 m for the radar’s operating frequency of 76.5 GHz. The RCS variation is about ±10.5 dB without the Rayleigh-based correction, i.e., using Eqn. (1), whereas it drops to about ±4.5 dB with the Rayleigh-based correction, i.e., Eqn. (3). The residual variation in RCS after Rayleigh-range correction may be due to orientation effects.

For example, the rear of the car may have been less perpendicular to the radar beam when the inferred RCS dropped below ~5 dBsm. Finally, when emulating road scenes, the additon of a stochastic term to Eqns.

(3) and (4) can help account for the signal strength fluctuations seen in the real world.

The standard deviation in decibels of such a term may even be chosen to depend on road conditions, e.g., dry and smooth versus gravelly versus snow-covered, etc. If anisotropic RCS data are available for objects – bicycles/bicyclists come to mind – then target orientation effects can be included into the equations to also improve signal estimation.

8 • 2022

All in all, the classic 1/R4 “law” relating radar roundtrip signal strength to target distance and RCS is not really a law at all but rather an approximation. Even discounting real-world road effects such as object orientation, ground bounce multipath, etc., the approximation is only valid at sufficiently large distances. It grossly overpredicts signal strength at close distances; conversely, automotive radar software which misapply the classic formula at close distances will underpredict target RCS. Equations which are more faithful to diffraction physics reduce signal=strength estimation error or conversely RCS error.

Acknowledgments —The author would like to thank his colleagues in Keysight’s Autonomous Drive Emulation team for support - especially Christian Bourde and Sven Leitsch, along with extra thanks to Bernhard Holzinger for supplying the vehicle target data in Figure 1.

references the invention of radar, https://en.wikipedia. org/wiki/robert_watson-watt radar monitoring of bird migration, https://birdcast.info/migration-tools/livemigration-maps radar return signal strength equation, “introduction to radar systems”, 3rd edition, merrill i. skolnik, mcgraw-hill, 2002. friis formula, see, e.g., chapter 12 in “fields and waves in communication electronics”, s. ramo, j.r. whinnery, and t. van duzer, john wiley & sons, 1965. more on signal strength variability, “analysis of multipath and doa detection using a fully polarimetric automotive radar”, t. visentin et al., proc. of 14th european radar conference, 11-13 october 2017, nuremberg, germany, pp. 45-48. figure a7 in https://cdn.euroncap.com/ media/39159/tb-025-global-vehicle-targetspecification-for-euro-ncap-v10.pdf gaussian beams, See, e.g., chapter 6 in “quantum electronics”, 2nd edition, amnon yariv, john wiley & sons, 1975. more on object classification, “radardetection based classification of moving objects using machine learning methods”, v. nordenmark and a. forsgren, master of science thesis mmk 2015:77 mda 520, kth industrial engineering and management, machine design, se-100 44 stockholm, sweden.

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designing-in “safe” rf levels

new ics sense human proximity to keep the rf output of consumer devices within safe levels. david wong, semtech, wireless and sensing products group

whether

for personal

proximity sensing basic block diagram

consumption

or work, wireless devices are used daily. As the number of devices continues to grow, they must provide robust connectivity and ample battery life while also complying with industry regulations.

Mobile equipment manufacturers are designing wireless devices that deliver higher throughput to bring better consumer experiences. In 1996, the Federal Communications Commission (FCC) adopted practices to ensure RF-enabled consumer devices adhere to regulated levels of RF output power in the presence of a human body. These limits are rated in terms of Specific Absorption Rate (SAR), which is a measure of the amount of RF energy absorbed by the body when using a wireless device.

In the U.S., the FCC sets the exposure limit for the general public to be a SAR level of 1.6 W/kg (over 1g of tissue) with a separation distance of 25 mm from the user. The European standard is 2 W/kg (over 10g of tissue) with a separation distance of 5 mm from the user. Each new product must be tested for compliance before it can be shipped to consumers. That is the reason for the development of intelligent sensors. With intelligent sensors, OEMs can help deliver better consumer experiences by offering not just automatic compliance with SAR levels, but also a variety of other benefits, including better performance and RF connectivity for connected devices. These sensors intelligently sense human presence near a mobile device and enable advanced RF control when a user is close by—delivering high-quality connectivity in consumer smartphones, laptops and tablets exactly when consumers want and need it.

When designing consumer devices, incorporation of smart sensors enable a device to meet SAR compliance requirements while maintaining peak device performance. For example, a smart sensor will lower RF output power if the user holds the phone while using it. If the phone sits on the table while the user makes a call via a wireless headset, the RF output power can remain high, thus ensuring

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the basics of an sx9330 sar engine chip. the sensor can be a simple copper area on a pcb. its capacitance (to ground) varies when a conductive object is moving nearby. the analog front-end (afe) performs the raw sensor capacitance measurement and converts it into a digital value. the digital processing block computes the raw capacitance measurement from the afe and extracts a binary proximity status, i.e. object is “far” or “close”. it also triggers afe operations (compensation, etc). a robust connection. Alternatively, a smart sensor built into a laptop would deliver higher connectivity performance in a Zoom meeting if the user is not typing on the keyboard.

As the wireless market advances further, more and more mobile phones will support 5G networks. A September 2021 report by analyst firm IDC predicted that by the end of 2022, 5G units could make up more than half of all smartphone shipments.

One challenge with 5G smartphones— because they have, on average, six antennas to handle both 5G and legacy network requirements—is maintaining SAR compliance.

In addition, 5G smartphones streaming video— among the most performance intensive tasks for a phone—are expected to account for 73% of all mobile data traffic by 2023. Through use of smart sensors, OEMs can deliver high-quality 5G/Wi-Fi 6 connectivity and ensure users get the best experience from their devices.

inside a smart sensor

To understand the workings of a smart capacitive sensor, it is helpful to review the functions of one such device, a four channel SAR controller (SX9330). It accepts four sensor inputs and can accurately discriminate between

8 • 2022

proximity effect on electrical field and sensor capacitance

when no conductive object (finger/palm/ face, etc) is within range, the sensor only sees an inherent capacitance value cenv created by its electrical field’s interaction with the environment, in particular with ground areas. when the conductive object approaches, the electrical field around the sensor is modified and the total capacitance seen by the sensor rises by the amount of user capacitance cuser.

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S A F E R F L E V E LS typical application circuit a typical application circuit for the sx9320 chip.

an inanimate object and a human body. When the chip senses a human body nearby, it sends an alert via an I2C serial bus to its host processor to indicate detection. The sensor input can be relatively simple and is often not much more than a copper plate on a PCB that is surrounded by a ground shield for noise immunity. Both the plate and the ground shield are connected to separate inputs to the SX9330 device.

The sensor detects the presence of a conductive object usually a finger, a palm, and so forth. When there’s no conductive object close by, the sensor only sees an inherent capacitance value created by the interaction of its electric field and the environment, in particular, nearby grounded areas. An approaching conductive object modifies the electric field around the sensor, and the total capacitance the sensor sees will rise.

The SX9330 contains an auto-calibrator that regularly adjusts sensor sensitivity for changes in temperature, humidity, and electrical noise. To save power, and because proximity events are relatively slow by nature, the chip is idle most of the time, only awakening for regularly programmed scan periods.

According to the tech product review site Tom’s Guide, most consumers keep their smartphones for up to three years. This means phones designed today must be able to work with a wide range of wireless protocols—from 5G sub-6 to Wi-Fi 6 to emerging mmWave networks—if they are to be future-proofed. In the coming three years, predictions are that more than 1.6 billion PCs and tablets will be sold. Furthermore, the 16.3% of consumers worldwide who do not own a smartphone today will likely purchase one, and 72% of all internet users will solely use a smartphone to access the web. Integrating smart sensors into connected devices provides the most sensible path to optimal connectivity and maximizes system performance in every wireless device.

references semtech, www.semtech.com/

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evolving radar technology in adas

even lidar may become unnecessary thanks to advances in highly integrated rf chips.

prajakta desai, texas instruments

over

the years, the application of radar within the automotive

industry has improved both safety and convenience. Radar can work in extreme environmental conditions such as rain, snow, dust and bright sunlight and also provide precise distance and velocity information.

Consequently, radar is considered the most appropriate sensing method to meet New Car Assessment Program (NCAP) requirements.

(NCAP is a government car safety program that aims to evaluate new automobile designs for performance against various safety threats.)

Radar sensing has become a cost-efficient sensing method for advanced driver assistance system (ADAS) functions and to meet Society for Automotive Engineers vehicle autonomy levels 2+ and even 3+. Radar sensors with higher ranges and resolution are evolving to handle more advanced levels of automated driving. And because radar sensors can now support multiple functions, they help on-board controllers better manage space around the vehicle.

Up to level 3+ autonomy, vision and radar sensing can address the requirements economically. (However, wheel speed sensors as used for ABS and related functions will still be required.) For level 4 and beyond, vision, radar, and lidar might be necessary. Radar sensors, when built with cascaded transceivers (a higher number of virtual channels), offer lidar-like performance (higher angular resolution), but at the right cost point.

However, the process of safely turning, changing lanes, navigating tight corners all present significant design challenges for advanced vehicle autonomy. In particular, there are technical barriers associated with getting the visibility around corners necessary for designing high-quality ADASs and parking assistance, as well as for broader adoption of autonomous vehicles. Being able to see farther and more clearly with radar leads to improved sensor fusion for safer automated driving and parking. In addition to the performance that radar brings to the table, the key advantage of radar for an ADAS is its ability to operate

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reliably regardless of weather conditions.

In particular, 77- to 81-GHz millimeter-wave (mmWave) long-range radar sensors from Texas Instruments offer the ability to detect objects in a wide geographical area out to 200 m. Mid-range sensors operate in the range of 100 - 150 m, while short-range sensors use transceivers, with signal-processing equipment mounted behind the bumper, track an object or person 30 - 50 m from the vehicle. CMOS technology has enabled Level 2+ 5 sensors

Front: 1 short range 1 medium range Rear: 1 short range 1 medium range 1 long range

the awr1843aop provides a wide field of view in both azimuth and elevation that enables true 3d detection for various objects as depicted in this comparison of range and field-of-view for ultrasonic vs. mmWave radar systems.

autonomy levels and their corresponding sensing requirements.

Level 3+ 7 or more sensors

All of the sensors named above for front and rear Plus sensors on each side of the car for 360-degree coverage

Level 4 and beyond All sensing modalities

Front: Short- and medium-range sensors Rear: Short-, medium- and long-range sensors Sides: May include all sensing modalities including cameras, radar and lidar

8 • 2022

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RA DA R F O R A DA S resolution is 4 cm (versus 75 cm for 24-GHz radar). Moving forward, most automotive radar sensors will likely shift to the 77-GHz band.

Smaller sensor size is another advantage of higher radar frequencies. For a chosen antenna field of view and gain, the area of the antenna array can be approximately three times smaller than that for 24 GHz. This size reduction is particularly useful in automotive applications where sensors must sit in cramped quarters behind the bumper, in doors and trunks for proximity applications, and inside the cabin for occupant sensing and similar tasks.

as good as lidar a radar front end with a high level of integration.

For short-range radar, the 24GHz narrow and ultrawide (>500 MHz) bands have been used in legacy automotive sensors. For simple applications such as basic blind-spot detection, you can use industrial, scientific and medical (ISM) band. (Specifically the 2.4 GHz ISM band, because of the readily available and inexpensive wireless ICs working at these frequencies.)

But in most cases, including ultra-short-range radar applications, the need for high resolution dictates use of the ultrawide band.

This band is being phased out, however, because of spectrum regulations and standards developed by the European Telecommunications Standards Institute and the U.S. Federal Communications Commission.

The 24-GHz ultrawide band became unavailable as of Jan. 1, 2022, known as the “sunset date,” both Europe and the U.S.; only the narrow ISM band will be available in the long term. This lack of wide bandwidth in the 24-GHz band, coupled with the need for higher performance in emerging radar applications, makes 24 GHz unattractive for new short-range radar implementations.

There is a 76 to 77-GHz band available for vehicular long and mid-range radar applications.

This band has the benefit of a high allowed equivalent isotropic radiated power. (The total power needed for an ideal isotropic antenna to produce the same power density as a beam antenna.)

The power level is sufficient to enable front long-range radar applications such as adaptive cruise control. The 77 to 81-

GHz short-range radar band has recently gained significant traction for uses in industry.

One key benefit of 77 GHz radar is its wide sweep bandwidth, 4 GHz. The range resolution of a radar sensor signifies the minimum dimension to which it can distinguish two closely spaced objects, whereas the range accuracy represents the accuracy in measuring the distance to a single object. Range resolution and accuracy are inversely proportional to the sweep bandwidth. More specifically, with FMCW radar used in vehicles, the frequency change over a given time limit determines the resolution. Thus, due to its ability to accommodate a faster frequency shift, a 77-GHz radar sensor can realize 20 times better performance in range resolution and accuracy compared to 24GHz radar. The achievable range

In current ADASs, primary safety measures such as automatic emergency breaking (AEB), autonomous emergency steering (AES), automatic cruise control (ACC) and forward collision warning (FCW) are considered basic features and are mandated by regional NCAP regulations.

As technology progresses, ADASs incorporate more crash avoidance and safety measures.

These safety measures depend on the sensors in the underlying systems. Original equipment manufacturers (OEMs) and Tier-1 suppliers pay close attention to the sensor suite for these functions, specifically ensuring that sensors meet the stringent requirements of NCAP tests. And traditionally, the sensor technology used for pedestrian avoidance, lane-change warnings, auto-braking solutions and adaptive cruise control applications has been lidar.

four main frequency bands are dedicated to automotive radar worldwide: 24 to 24.25 ghz, an ism band; 21 to 26 ghz, an ultra wide band; 76 to 77 ghz for automotive long range radar; and 77 to 81 ghz for automotive short range radar. european automakers have been using the 24 ghz band for automotive radar, but that practice will be discontinued this year.

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES Automotive lidar sensors use light reflected from targets to gauge distance, velocity, and perhaps other features. Lidar sensors can detect objects nearly 200 m in front of the vehicle.

High cost is a primary concern when using lidar, however. Fortunately, the combination of vision and radar sensing can cost-efficiently address requirements to autonomy level 3+; but it may take these methods combined with lidar to handle level 4 and beyond.

Consider a sensor configuration in which multiple TI AWR2243 sensors are cascaded together. This assembly operates synchronously as one radar unit, with many receive and transmit channels. The result is significantly enhanced angular resolution as well as better radar range.

Cascaded together, mmWave sensors can reach an extended range of up to 400 m using integrated phase shifters to create beamforming.

Radar sensors built with cascaded transceivers (effectively providing a higher number of virtual channels) offer lidar-like performance (higher angular resolution) at a lower cost.

One place where cascaded radar sensors excel is in identifying static objects with a high resolution. This contrasts with the typical mmWave sensor which is limited in IDing objects standing still.

new applications

To get a 360º surround view of the vehicle environment, auto manufacturers must integrate sensors into small spaces such as door handles or B-pillars. The small form factor of TI’s AWR1843AOP antenna-on-package (AOP) sensor facilitates this process. TI’s AOP mmWave radar sensor integrates the antenna, radar transceiver, digital signal processor, microcontroller and interface peripherals onto one chip. So there is no need for a high-frequency PCB substrate. And the fact the antenna is built-in eliminates antenna development work that speeds time to market.

Today, surround-view cameras and ultrasonic sensors enable parking assistance. But drivers still must make judgments and maneuver based on sensor feedback. To enable parking that is completely automated, the sensor should be capable of detecting other cars, curbs or

pedestrians from 3 cm to more than 40 m away in a wide field of view, despite weather conditions.

In that regard, mmWave sensors can detect smaller nearby (<25 cm) objects (such as a metal rod protruding from the ground) that other sensing methods might miss, all while functioning under a variety of weather and lighting conditions. Radar sensors also improve vehicle aesthetics because they operate without the need of bumper holes.Radar sensors can also detect what goes inside the passenger compartment. Driver monitoring systems, seat-belt reminders and airbag deployment are all candidates for radar sensing.

Heavy objects laid on a seat need no longer trigger seat-belt reminders.

Airbags could deploy at different speeds to accommodate small children. Absent-minded drivers could receive reminders that infants or children are still inside vehicles because radar detects lifeforms more accurately than any other sensor technology.

Radar sensors can also detect drowsy drivers by estimating heartbeat and breathing rates. In fact, a single sensor can monitor vital signs for all occupants and generate alerts about their medical issues.

Also, radar sensors can detect gestures such as the swipe of a hand or twirl of a finger so drivers needn’t take their eyes off the road to fumble for pushbuttons or knobs. Ditto for movie-watching passengers in second row who would no longer need to extend their hands toward a screen to touch a knob.

the 77-ghz antenna array is significantly smaller than that for 24 ghz.

references ti.com/radar

the angle resolution needed to see a truck parked under a bridge 100 m away.

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bootloaders for arm cortex-a35/a5x mpus it pays to know the benefits of bootloaders for the arm cortex mpu s which have long formed one of the backbones for embedded automotive applications. aaron bauch, iar systems

design

specifications require the

ability to dynamically update a device’s firmware in the field.

This takes place commonly via a bootloader. The process of designing a bootloader, however, is challenging; this software must meet a wide variety of requirements. For example, in some situations, the mechanism for getting the new application into the MPU is through the USB peripheral. Yet for others, it might be Over the Air (OTA). When creating a bootloader, there are several questions to consider regarding project setup and the execution handover from the bootloader to the application.

Some of these include: Should you have one single project, or one for the bootloader and a separate one for the application?

When and what is the best way to perform the hardware initialization?

What about configuring or resetting the stack pointer?

How do you avoid unexpected interrupts during startup?

How can you map the memory for the bootloader and allocate enough memory for the application?

In addition, the process of debugging a bootloader can be tricky because there is only source-level access to either the eeworldonline.com

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bootloader or the application at debug-time. The challenge is how to make the debugger aware of the two “applications.” But first, let’s start with the basics.

MCU Address Space 32-bit/64-bit bootloader configuration word is @ 808001FCh User page is @ 80800000h

what is a bootloader?

A bootloader is a standalone program that's generally the first code to run on a processor at startup. It loads essential software to get the minimum running on the processor chip before higher-level software can run. The tasks performed by embedded bootloaders vary based upon the architecture and the application. Based on several criteria, they decide whether to jump to the installed application and start running or to load a new application that may include updated firmware for the system.

Bootloaders provide the ability to do field upgrades of system firmware and, in some cases, protect against invalid code rollback and other attack mechanisms. (As a quick review, a rollback attack replaces the current secure storage data with an older valid version to, for example, bring back old keys/ credentials which were replaced or remove keys/credentials.)

Bootloaders can range from simple to quite complex, depending on the functions required. It's wise to consider the many commercially available bootload-ers before writing custom code for a specific application.

While a bootloader can update application firmware, it is

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Flash User Page

512 B

Free Flash Space

504 kB Application

Application is @ 80002000h Reset vector is @ 80000000h

Bootloader

challenging to update a bootloader in the field, making it essential to select the right solution.

Modern embedded systems generally have extremely complex firmware which requires frequent updates for various reasons.

Reasons for updates include adding functions to existing systems, fixing bugs in existing code, or keeping systems up to date. It is common for a system to include a firmware update as part of the device installation. The proliferation of re-programmable on-chip program storage, such as flash memory, helps enable this feature.

A bootloader performs various hardware checks, initializes the processor and periph-erals, and completes other tasks like partitioning or configuring registers.

In addition to starting up a system, bootloaders can update MCU firmware every time the MCU/

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512-kB Flash Array

8 kB

a memory map of a system that uses a bootloader for startup and management. this example shows an stm32 arm microcontroller which has its program starting at memory location 800000 hex. in this case, the bootloader and its interrupt vector table are populated at the primary program base address. The main application resides at some higher address, starting with the application program’s vector table, which contains a jump vector to the start address of the application. this leaves space at the bottom of the flash memory for the bootloader code.

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES bootloader as a fixed part of the target chip and not as part of something else. Once the bootloader is debugged and in place, you can download and debug the application without worrying about the load or startup mechanisms implemented in the bootloader.

debugging bootloaders

application and bootloader projects displayed in the same workspace.

MPU resets or when the MCU/MPU resets and a button on the physical device is pressed. In addition, it can be a mechanism for initial device programming on the production floor. Because a bootloader is a separate program that runs at the system's startup, it can perform a diverse range of setup and check functions or jump to an installed application. The latter is the most common function.

Once the application starts, there's no reason why the application must be aware that the bootloader launched it. The bootloader often runs in the context of other startup code, such as memory initialization routines, before an application reaches the primary function start point in a C or C++ project.

The process of setting up a bootloader project is no different from that of any other project done via Integrated Development Environments (IDE) like Embedded Workbench from IAR Systems. Initially, developers should create a basic framework for a new project that will ultimately become the bootloader for

the system. Alternatively, users can create a bootloader using chip initialization tools, which will create the bootloader project in a separate workspace. This project can be added as an existing project to the application workspace, making it easy to work on them together.

So far, we’ve assumed that the preferred way to implement this combination of functions is through two separate projects, one for the application and the other for a boot-loader.

However, this approach is not arbitrary. There are good reasons to set up the environment in this manner.

It's possible to combine the bootloader and application into a single project, but this approach has several drawbacks. Foremost is the challenge of making changes. Tying the two functions together in one project means changes made to one will affect the other. In addition, this approach can cause significant inefficiencies in how memory gets allocated and viewed.

In contrast, it's best to think of the

In general, the process of debugging the bootloader can be tricky because developers can access either the bootloader or the application at one time. Some IDEs provide the ability to load multiple images (ELF/ DWARF, executable and linking format/ the debug-ging file format often used by compilers and debuggers to support sourcelevel debug-ging) or only load the debug symbols to have a smooth bootloader-toapplication jump debug transition.

When debugging the bootloader-especially when checking the transition to the start of the application--there are tradeoffs.

This is particularly true when a developer wants more than just the application's binary image loaded. For example, it may be helpful to download the symbol information from the application and the symbol information for the bootloader. This action would enable the developer to view the source-level information, such as line numbers and symbol references, as it transitions from the bootloader to the application.

The benefits of having symbols from both projects together can be quite helpful so long as there is an understanding of the issues introduced by loading multiple projects’ symbol information. For one thing, some

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E M B E D D E D AU TO M OT I V E SYST E M S

steps involving in setting up a debugger to load the symbols from the application found in the ELF output file from the application project. note that the address offset is set to zero because the symbols in this file have the correctly located absolute addresses of code and data for the application. in addition, checking the debug information-only box ensures that the debug symbol information and the program image are down-loaded separately and linked as a binary file to the bootloader program image.

warnings may be ignored.

Downloading both the bootloader and application images, and the symbol information for both of them, can enable source-level debugging of the bootloader and then of the application. This process helps developers ensure the jump from one to the other hap-pens correctly. And it may be used to verify only the start of the application code while debugging the bootloader.

With this verification complete, developers can finish debugging the application without loading the program or symbol information for the bootloader. Proceeding this way al-lows extensive application debugging without any issues of redundant lead-defined symbols. The bootloader can be installed and run as part of the startup code of the sys-tem before the main application starts.

safe and secure bootloaders

As mentioned earlier, the array of possible functions performed by a bootloader can be quite extensive, due primarily to the fact that it is the first code to run on the processor in the system. As such, it's also the ideal place to implement a security protocol for the installation of new firmware updates. It is essential to ensure that any new code in-stalled comes only from a trusted source. This requires that the code update be signed for authenticity, which the target bootloader can check before installation.

The entire update may be encrypted to prevent third parties from viewing or stealing it in transit.

And the target system must contain secret key information to validate and decrypt an image before installation.

Finally, it's desirable to have rollback protection so an attacker cannot install an old ver-sion of the device firmware, such as a valid image known to have vulnerabilities, which was subsequently fixed and updated. This rollback protection prevents a hacker from exploiting known and fixed vulnerabilities by installing older firmware versions.

All these capabilities add complexity to the bootloader, which will suggest that using proven debugged and robust bootloader code for these applications is likely a good choice.

The use of bootloaders in today's embedded systems--which increase in complexity daily--is increasingly common.

Bootloaders provide the ability to deliver firmware up-dates after product delivery and create opportunities for adding features and fixing bugs throughout the product life cycle. The creation of a bootloader can be a challenging task; however, modern commercial toolchains make this process manageable and straightforward.

The debugging of bootloader functions—particularly those involved in the transition from the end of the bootloader to the start of the system application code-requires an advanced debug environment that makes the validation of bootloader operations a standard exercise.

references iar systems, www.iar.com

downloading the bootloader and application images, and the symbol information for both, can enable source-level debugging of the bootloader and then of the application.

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design tips for high-voltage protection in evs and hybrids

the primary goal of ev protective circuits: keep vehicle occupants safe day-to-day and first-responders safe if the worst happens. michael zimmerman, littelfuse, inc.

the

12-V automotive battery may become a relic of the past as

electric vehicles (EV) and hybrid cars gain market share. EVs and hybrid vehicles use battery packs of at least 500-V and some reach

the energy that can short to the vehicle body through a load circuit failure. The actions are: • •

1,000 V. The higher voltages are required to power electric drive motors efficiently.

However, the potential danger to vehicle occupants—or to anyone who comes in contact with a vehicle—is more significant when high

•

Disconnect the battery from the load circuits to de-energize them.

Provide a high-speed disconnect method for the battery that energizes in the event of a catastrophic failure like a hard battery short circuit.

Discharge high-voltage capacitors and related energized systems to ensure safe voltage discharge.

voltages are present.

The high reactivity of metal Lithium has brought considerable attention to battery safety. A battery management system (BMS) is necessary to safely operate a lithium-ion battery. The BMS monitors at least the state of each cell’s voltage and temperature and controls the equalizing currents, ensuring all battery cells connected in series have the same voltage. Highly developed systems also enable continuous monitoring of individual cell stateof-charge through permanent analysis of the energy flow during charging and discharging.

In particular, high-performance lithium-ion batteries can see high short-circuit currents initially because thee batteries have a low internal resistance.

Lithium-ion batteries’ prospective (unaffected) short-circuit current is several times (about 5 to 10 times) that of other batteries, e.g., lead-acid batteries. The high value also makes the magnitude of the short-circuit current rise much faster than in conventional batteries because the electrical time constants are about the same – in the range of milliseconds.

To keep individuals safe from a short circuit and high voltage in an EV or hybrid vehicle, the primary requirements are disconnecting the high voltage energy sources from all loads and discharging any stored high voltage.

Designers can design their circuitry to take three actions that will protect individuals from

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When protecting against short circuits in dc circuits, the following problems arise: In many cases, circuit breakers with magnetic or thermal overcurrent detection are too slow. Disconnection takes place only after a high battery discharge current is already flowing, and the circuit breaker is overloaded and may be damaged by high energy.

DC-capable fuses can serve as shortcircuit protection but must be replaced once the source of the short-circuit has been

an example pyro switch module, showing the position of the module’s piston above the battery distribution unit busbar. found. In many cases, lengthy replacement times are impractical, and the fuse design is challenging. Still, fuses are the most reliable way to prevent catastrophic failure and enable a higher safety level. Companies like Littelfuse offer application engineering support and a wide range of fuse products for voltages ranging from 500 V to 1,000 V. For example, the Littelfuse 828 cartridge fuses and EV1K

a battery distribution unit diagram shows the position of the contractors, the pyro switch, the current sensor, and the high voltage fuses.

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V E H I C L E E L E CT R I CA L P R OT E CT I O N occupants would be at risk here.

Such scenarios show why it is necessary to disconnect the battery from load circuits when there is a catastrophic failure. Anticipating such conditions, designers should ensure highpower circuits have incorporated fast overload protection. The battery can deliver, almost instantaneously, potentially up to 30 kA during a short-circuit failure. High-voltage fuses have current interrupt ratings below 30 kA and an opening time of up to 50 msec. Consequently, they can’t open fast enough to prevent the massive current rise and protect against potentially irreparable damage. The battery distribution unit needs a better solution, which is a pyro switch.

high-speed circuit interruption

response of a pyro switch and current sensor/triggering unit (ecx) to an overload current surge. The pyro switch keeps the fault current from reaching a peak level and breaks the circuit in under 1 msec. The diagrams below the plot show the pyro switch’s physical state over the time interval from detection of the fault current to the breaking of the busbar. (test conditions: 500 v, 30 ka, and 12.5 μ h). Modifications to the ecx can reduce the total interrupt time. semiconductor fuses can handle up to 1,000 V. In principle, many power electronic components are fast enough to switch the current off before it reaches critically high values in the event of a short circuit. However, these components have a comparatively small I²t value. (As a quick review, I²t is an expressoin of the available thermal energy resulting from current flow.) It is practically impossible to realize selective short-circuit clearing in a dc

network with devices have a small I²t value.

The interruption of high dc currents—not easy in any case—has gained new emphasis with the adoption of powerful lithium-ion batteries. Ordinary dc protective devices usually don’t do the job here. Automotive standards require that EV and hybrid vehicle circuitry prevent a battery pack failure from damaging the vehicle and its controls.

In addition, electronics engineers realize their designs must protect people in the event of an accident. Any kind of accident could result in damage to the vehicle electronics. For example, an inadvertent connection between a high-voltage battery bus line and the metal exterior of a vehicle can cause a fatal electric shock. First responders as well as vehicle

use of a thyristor-resistor component configuration in a discharge switch for discharging high voltage capacitors.

A pyro switch is a protection component capable of interrupting 30 kA of current from a high voltage source in under 1 msec. A current sensor detects the current overload and triggers the pyro switch to break the busbar connection in the battery supply line. The current detector’s signal activates an igniter that produces a high-pressure gas that moves a piston down on the busbar. The gas pressure is high enough to cause the piston to punch a hole in the busbar. The hole diameter is sufficient in size so the arc, caused by the breaking of the busbar, is extinguished.

In a battery distribution unit, contactors connect and disconnect the battery during normal operation. The pyro switch and the current sensor sit close to the battery pack to detect a current overload and break the bus bar supply line in the event of a catastrophic failure. The loads have individual contactors and fuses for control and overcurrent protection. A discharge circuit removes voltage from highvoltage capacitors in the electronic sub-systems.

When selecting a pyro switch and current sensing unit, consider selecting a pair with: • •

•

•

•

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A voltage rating higher than the voltage of the battery pack A modular package containing a current sensor and a controller circuit to save space and economy An internal resistance under 100 µΩ to minimize power consumption during regular operation An option for including a fuse in the assembly for protecting loads from minor overload current failures CAN-Bus interface to communicate the state of the battery pack

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For more protection, designers can add fuses in the battery distribution circuit. Fuses can protect against overcurrents during overloads that do not lead to catastrophic surge currents.

Fuses can also protect EV wire harnesses and the charging cable. Fuses used in this circuit must have ratings that exceed the battery voltage. Consider using fuses that have: • •

• • •

A voltage rating of 500 V or, if required, 1,000 V At least a 10 kA interrupt rating at 1,000 V for lower-rated fuses up to 30 A Up to 30 kA interrupt rating for higher rated fuses Nominal resistance under 10 mΩ At least an opening gate of 500% of the rating, depending on the protection needs.

Filter capacitors across the battery will charge up to the battery pack voltage. An

accident and the disconnection of charged capacitors from the main battery can still cause high voltages in the system. So designers should provide a means of discharging these capacitors.

The discharge-switch circuit must handle high load currents and an occasional overload. The discharging function must stay operational over a wide range of environmental conditions during the vehicle’s life. Also, the discharge function should activate via a simple trigger control signal.

Consider using a thyristor-resistor discharge circuit across the high voltage capacitors. Resistor values should be such that they control the peak discharge current and have a low RC time constant for a fast discharge time.

Thyristors can provide a high surge capacity, superior heat dissipation, and better mechanical durability than MOSFETs or IGBTs. Furthermore, thyristors have a failure mode in which they short out under certain surge conditions, allowing a capacitor to discharge even if the thyristor has failed.

Look for thyristors with: • • • •

Current surge capacity of 500 A or greater An on-state current of 25 A or greater Voltage rating greater than 500 V AEC-Q101 qualification.

The top priority for those who design EV and hybrid electronics must be the safety of vehicle occupants and the personnel assisting with an accident. Designers can save precious development time by consulting protection component application engineers. They can assist with component selection and provide guidance on standards compliance. Also, some manufacturers offer pre-compliance testing to save time and minimize the cost for product certification.

references littelfuse, www.littelfuse.com

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES

the basics of dielectric resonator antennas the mmwave equipment on connected vehicles is likely to sport dielectric resonator antennas that don’t look anything like conventional antennas. leland teschler, executive editor

automotive

designers

probe-fed cylindrical dra

dra cross section

have always

put a premium on technologies that are lightweight and compact. The preference hasn’t changed for connected vehicles. As connected features increasingly rely on mmWave frequencies, designers investigate ways of shrinking the size of radio frequency (RF) electronics. In that regard, various antennas relying on monopoles, dipoles, and patch antennas have been proposed for millimeterwave use. However, these antennas typically have radiation efficiency problems and a narrow impedance bandwidth because of lossy silicon substrates.

Enter the dielectric resonator antenna (DRA).

It typically has a puck-shaped cylindrical shape rather than the radiating elements of the typical antenna. DRAs experience no conduction losses and can be highly efficient radiators. The first DRAs made use of ceramic materials characterized by high permittivity and a high Q (between 20 and 2,000). More recent DRAs are plastic poly-vinyl-chloride, PVC. DRAs are specialized versions of dielectric resonators. The dielectric material has a large dielectric constant and a low dissipation factor. (Recall that dissipation factor is the reciprocal of the ratio between the material capacitive reactance and its resistance at a specified frequency.) The resonant frequency is determined by the overall physical dimensions of the resonator and its dielectric constant. In a dielectric resonator, the RF is confined inside the resonator material by the abrupt change in permittivity at the surface so RF waves bounce back and forth between the sides. At the resonant frequencies, standing waves form in the resonator, oscillating with large amplitudes.

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Thus dielectric resonators resemble cavity resonators in their behavior. Cavity resonators are hollow metal boxes employed as resonators at microwave frequencies. Here RF reflections are via the large change in permittivity rather than by the conductivity of metal. Metal cavity resonators don’t work at millimeter wave frequencies because in this frequency range their metal surfaces become lossy reflectors.

Also of note is that while the electric and magnetic fields are zero outside the walls of a metal cavity, these fields are not zero outside the dielectric walls of the resonator. Even so, electric and magnetic fields decay considerably from their maximum values away from the resonator walls. Most of the energy is stored in

rectangular dra with transmission line and slot feed

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a typical setup for a cylindrical dra fed from a coax cable. the resonator at a given resonant frequency.

There are three types of resonant modes in dielectric resonators: transverse electric (TE, a magnetic field only along the direction of propagation), transverse magnetic (TM, the magnetic field is crosswise to the direction of propagation while the electric field is normal to the direction of propagation), or hybrid electromagnetic (HEM, both electric and magnetic fields have a component in the direction of propagation) modes. Theoretically, there is an infinite number of modes in each

typical setup for a rectangular dra fed from a slot aperture. the slot-feed is the most widely used method of exiting dras.

cross section

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a dra designed for actual use. researchers in brazil used the comsol cad program to model nano-dras on a nanostrip. at left magnetic field lines show the coupling compatibility between the fundamental nanostrip mode and dr’s he11 mode used in their work. at right, the lateral view showing the feeding geometry and respective thickness parameters. of the three groups, and desired mode is usually selected based on what the application needs.

To see why DRAs can be smaller than conventional antennas, consider that a metallic antenna size is proportional to the wavelength of its resonant frequency in free space. In contrast, the size of a DRA is proportional to the free-space wavelength divided by √ϵr where ϵr is the relative permittivity of the DRA material. Thus to shrink the DRA, use a material having a high ϵr. The use of a low-loss dielectric material also

gives DRAs their high radiation efficiency. And a DRA antenna can be made with a relatively large bandwidth by adjusting the dimensions of the device and the material dielectric constant.

The resonant frequency of the modes that a given cylindrical DRA supports is a function of the resonator height, radius, and dielectric constant. The equations for specific resonant frequencies involve roots of Bessel functions and their derivatives. Bessel functions are a standard solutions of a differential equation known as Bessel’s differential equation.

Bessel functions are often described as a way of describing vibrations in a medium with variable properties, which is why crop up in describing DRAs. Though cylindrical DRAs are probably the most widely used, rectangular DRAs are also common. The main advantage of the rectangular shape is that it offers more design flexibility than cylindrical types through adjustments to height, length, and width dimensions.

Rectangular DRAs also have less cross-polarization than cylindrical types. (Cross Polarization is the polarization orthogonal to the desired direction. If the antenna field are meant to be horizontally polarized, the cross-polarization direction is vertical. If antenna waves are right-hand circularly polarized, the cross-polarization is left-hand circularly polarized, and so forth.) The DRA resonant frequency in this case is a function of the square-root of the sum of the length, width, and height dimensions.

It is as well possible to find hemispherical and cross-shaped DRAs and DRA arrays. Crossshaped DRAs tend to be used to obtain circularly polarized waves.

fundamental parameters of a dra devised for use by researchers in brazil. the graph depicts return loss, s11, as a red solid line and gain in a dark-blue solid line. at right, the 3d radiation pattern at 193.5thz (1.55 µm) with broadside behavior.

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Arrays of cross DRAs can be used to get a larger antenna bandwidth.

Similarly, what are called super-shaped DRAs can be found.

These are DRAs with a more complex 3D shape, usually done as a way increase the antenna bandwidth. An example of a supershaped DRA might be one where the basic shape is cylindrical but instead of a curved side, there are eight flat sides.

One aspect of DRA technology is that specific radiating modes can be excited depending on where RF is fed into the DRA device. (Probe-fed DRAs aren’t practical when the DRA is made on a PCB or is integrated on an IC.) Probably the most common configuration for discreet DRAs is that where the DRA sits on a ground plane and is excited by a coax cable fed through the substrate. Interestingly, the coax probe can penetrate the DR but it can also be placed directly next to it. Adjusting the length and position of the feeding probe tunes both the input impedance of the DRA and its resonant frequency.

The main benefit of using a probe feed is that it couples a high amount of signal into the DRA which, in turn, leads to high radiation efficiency. The downside of this approach is that a hole must be drilled into the DRA material that precisely matches the length and radius of the probe.

Slight mismatches can change the dielectric constant of the resonator and shift the antenna resonant frequency. Placement the probe next to the DRA, rather than inside it, is less sensitive to dimensional mismatches but couples less signal into the antenna.

Another way to feed the DRA is via printed transmission lines. In conventional microstrip line-fed DRAs, the dielectric resonator sits directly on the transmission line printed on the PCB substrate.

The overlap distance on the printed conductor determines the coupling strength and the specific

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AU TO N O M O U S & C O N N E CT E D V E H I C L ES transmission mode that is excited. The strongest coupling is when the overlap distance is slightly shorter than one-quarter wavelength of the dielectric resonance frequency.

The main drawback of the microstrip transmission line feed is that the transmission line is not isolated from the DRA which can affect the radiation performance of the DRA. Also, when the dielectric resonator sits on the top of a transmission line, there’s an air gap between the resonator and the PCB substrate which can degrade antenna performance.

The other way of devising a microstrip transmission line feed is to place the DRA on the PCB and extend the PCB transmission line trace from the board to one of the outer sides of the DRA. This approach eliminates the air gap arising when the DRA sits on the microstrip transmission line. The shape of the transmission line can be optimized to improve the DRA performance, usually in terms of the antenna bandwidth.

Another approach is the coplanar-waveguide (CPW)-fed DRA. The coplanar waveguide can take the form of a circular-loop or capacitive or inductive slot feed. The main advantage is that tweaking the coupling slot underneath the DRA can optimize the DRA performance. A capacitive slot, for example, can add a resonance so one resonance is associated with the DRA, another with the feeding slot itself. CPW feed structures are widely used for mmWave applications because the PCB ground plane separates the dielectric resonator from the lossy silicon substrate to yield high antenna efficiency.

The most widely used feeding technique for DRAs is via a slot in the ground plane, a method known as aperture coupling. Here the DRA sits on top of the PCB microstrip transmission line and there is a slot in the PCB ground plane that also sits under the DRA and is oriented at 90° to the transmission line. Energy from the transmission lines couples through the slot to the resonant modes of the DR. The best resonance (impedance matching) takes place with the DRA perfectly centered on top of the slot. The main advantage of this method is that it avoids a direct electromagnetic interaction between the feed line and the DRA which reduces spurious radiation from the feeding network and boosts the polarization purity of the DRA. The drawback of this approach is that it becomes impractical at lower frequencies; the slot length should be around a half-wavelength long at the resonant frequency, challenging at lower frequencies when the DRA must remain compact.

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cpw circular-loop feed for rectangular dra

a rectangular dra fed by a cpw circular loop with examples of capacitive and inductive slot geometries.

In general, the size of the DRA is inversely proportional to the dielectric constant (𝜖𝑟) of the resonator material. But use of a high 𝜖𝑟 also tends to limit antenna bandwidth. Multilayer DRA topologies are sometimes used to mitigate the bandwidth problem by optimizing the 𝜖𝑟 and height of each layer.

Some DRAs also contain a conducting plate strategically placed as a means of reducing antenna size. On a rectangular DRA, for example, a conducting plate might go on one of the outside antenna surfaces. The price paid for the size reduction is typically a reduced antenna bandwidth.

Another way of getting more gain out of a given DRA is to excite it at a higher-order resonant mode. This make the DRA electrically larger with respect to its fundamental resonant frequency.

references dielectric resonator antennas: basic concepts, design guidelines, and recent developments at millimeter-wave frequencies, https://www.hindawi.com/ journals/ijap/2016/6075680/ wikipedia dielectric resonator antenna page, https://en.wikipedia.org/wiki/ dielectric_resonator_antenna dielectric resonator antenna for applications in nanophotonics, https://opg.optica.org/ directpdfaccess/7c1f508c-6e3e-49209f55b3903d843d27_248410/oe-21-1-1234. pdf?da=1&id=248410&seq=0&mobile=no

8 • 2022

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hybrid sensors for connected vehicles the dependence of smart vehicle features on sensing technology has manufacturers thinking about how to field devices that combine functions in economical ways. leland teschler, executive editor

estimates

are that today’s vehicles can

have between 60 and 100 sensors onboard.

And over the next decade the number of sensors is expected to double. No wonder, then, there are efforts afoot to have one sensor to double or triple duty in connected vehicles of the future.

As an example of these efforts, consider the work of engineers at Tohoku Fujikura Ltd. (TFL) in Japan. They devised a combination SBR (seat belt restraint) sensor and seat heater.

It is interesting to review the steps TFL went through in devising this device.

Briefly, the SBR occupant detection sensor sends a signal when two electrodes facing each other touch because of pressure applied to the seat surface. The signal goes to an electronic controller unit (ECU) that determines whether or not a passenger is in the seat and, if necessary, tells the passenger to fasten their seatbelt.

There are two types of SBR sensors.

One sits on the upper seat just under the top surface leather (A-Surface). The other sits on the seat forming (B-Surface), basically, under the seat cushion. Though SBR sensors have long been required for front seats, a recent amendment to international car safety standards requires the installation of SBR sensors in all passenger seats.

To distinguish between a passenger and luggage, a conventional SBR device has

the two typical positions for a seat belt restraint sensor in a vehicle seat.

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DESIGN WORLD — EE NETWORK

a conventional sbr sensor. the switches sit at each end of the “H” shape. sbr sensors use multiple switches as a way to distinguish loads from packages and other debris from a human occupant. an H shape so it operates only when at least one electrode on the left and right side make contact. This reduces detection errors from factors such as shopping bags on the seat.

TFL engineers say the H shape also makes for reliable detection even if the seat occupants change their position or posture.

The A-Surface SBR sensor is about 0.3 mm thick and resides under the surface of the seat or back rest so it is relatively close to the passenger or to objects placed on the seat.

Its position gives the sensor a relatively large pressure load that is stable. However, TFL says there are issues associated with fixing the sensor precisely between the surface leather and the seat cushion foam. And passengers apparently can feel the sensor when they sit on it.

That brings us to built-in seat heaters designed to warm passengers. Conventional seat heating devices consist of one long electric heating wire about 1.0 mm in diameter arranged on the surface of a 2.0-mm-thick flexible non-woven cloth. The occupant detection sensor turns the heating operation on or off. To expand the heating area, the seat heater requires some thick buffer material between the leather seat covering and the cushion form to expand the heated area and make the heating wire unnoticeable to the passenger sitting on it. The problem is the buffer material also increases the amount of energy necessary to effectively heat the seat.

The combo seat heater/SBR sensor TFL

8 • 2022

engineers devised is soft and flexible enough to fit the base seat cushion form and puts the sensor electrodes on a printed conductive circuit.

To combine the SBR sensor and the seat heater, TFL developed a printed circuit woven (PCW) sheet composed of copper circuit printed on a glass cloth (GC) substrate. (Interestingly, TFL says the PCW sheet was originally developed for wearable application.) The heated area is about 10.25x9 in. The electrode on the GC is 0.1-mmthick screen-printing copper said to handle temperatures up to 300ºC. There are electric circuits facing each other on both sides of the GC that connect through holes between the warp and weft of the GC weave. A low-elasticity resin is applied to areas of the GC to form a substrate for printed circuit features making up sensor connections and electrodes. Conductive metal ink is selectively applied next to create the copper circuit traces on the GC comprising the heater conductive elements and to create the conductive electrodes on the resin. A second layer of low-elasticity resin is then applied to serve as a flexible protective coating for the conductive heating elements and the conductive circuit elements. TFL says the physical and mechanical properties, appearance, and environmental resistance of the PCW sheet can be adjusted C heating device

Slitting open

Core substrate (grass-cloth) PET printed circuit for sensor electrode

Upper Cu traces for heating device Heating activate zone Upper electrode of SBR sensor Upper electrode for general purpose sensor

Slitting open

CU circuit for sensing signal

Insulation layer

General purpose sensor (ex. pressure)

Polyimide flexible printed circuit (PI FPC)

Lower electrode of SBR sensor Lower CU circuit for heating device

PI FPC for wire soldering

a ghost view of the tfl prototype sbr sensor/heater. tfl engineers also left space on the surface holding the sbr electrodes for other sensors such as for sensing the physique of the seat occupant. engineers say these options will be explored in future work.

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the assembly steps involved in creating the substrates of the hybrid sensor/heater.

The “basket holes” refer to vacant areas in the woven substrate due to the weft and warp of the weaving process.

through resin coating, impregnation, and forming processes.

Like conventional SBR sensors, the hybrid device has upper and lower electrodes that face each other. The use of a GC substrate instead of conventional doublesided adhesive PET film minimizes the rigid area of the sensor so seat occupants are less likely to notice it.

The seat heater material is less than 0.15-mm-thick and is configured with a copper feeder circuit and a printed highresistance heating carbon film. The carbon film is formed by printing a high-resistance heating carbon ink on the both sides of the heating substrate fully overlapping copper feeder circuit. The heating device generates about 80ºC and the area around the SBR sensor gets up to around 40ºC. TFL says a variety of materials are candidates for use as surface protection material including non-woven or needlepunched fabrics. Thus the hybrid SBR/heater device can be used in leather seats as well as in seats with less expensive coverings.

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the completed sensor/heater hybrid as it appears in a seat, left, and its appearance on a thermal camera when in the process of heating.

references https://www.fujikura.co.jp/ eng/rd/gihou/backnumber/ pages/__icsFiles/

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