Radar Simulators

Radar technologies have grown significantly in the past 10 years due to commercial applications as well as advanced semiconductor technologies ASIC.

Validating functionality and performance of any wireless device between transmitter and receiver in the open air requires meticulous design of experiment and difficult to begin with.  Typically, multiple experiment must be done to capture adequate reliable information, in order to make assessment of that wireless device.

In case of radar, this validation is an order of magnitude more difficult, as the radar pulse and echo have to be captured in the open air.  There are many circumstances that measurements can have a very low yield.  Furthermore, that open air testing has high expense tag for every run and have to be repeated multiple times to have confident in the measurements.

Cost of testing any radar can range from couple hundred thousand to multi millions per year, depending on the platform to be tested and conditions of the testing.

Radars are used in aircraft, automotive, drone, ground base, ship, and train.

What is the alternative? Radar Simulators.

Radar system is comprised of HW, FW, and SW like any other radio system. To validate the functionality and performance these components, radar simulator can be used.

Radar simulator allows to various necessary algorithms, such as; gain control/dynamic range, direction finding, tracking, target identification.

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Radar KPI

Radio detection and ranging, radar key metric is probability of detection, Pd.

In radio communication QoS is probability of error, or error rate, BER or SER.

Radar probability of detection is directly proportional SNR, as in radio communication, BER is inversely proportional to SNR or Eb/N0.

As the SNR increases, the probability detection increases in radar.  Furthermore, radar has false alarm rate, PFA that needs to minimized.

Therefore, just like radio communication which has Water Fall Curves that describes digital alphabets required BER or SER to SNR or Eb/N0, radar has probability detection vs. SNR for given false alarm rate.

The radar probability of detection vs. SNR for given probability of False Alarm do not have analytical or closed form solution and it is typically plotted using numerical technique.

The classic Skolnik radar handbook has plots which show the non-linear relationship between these parameters.

Target tracking radar requires higher SNR than target acquisition and detection radar for given probability detection and false alarm rate.

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Swerling Radar Models

Radar target echo is distorted by scintillation of Radar Cross Section, RCS.

This is similar to fading of signal in radio communication systems.

As a result, target echo signal level can change drastically up to 30dB over short period of time.

Classical Swerling has 4 radar models which allow radar designer to validate the functionality and performance of the radar.

Swerling 1 model is utilized when the radar target RCS is slowly changing relative to dwelling time.  It follows the Rayleigh distribution.

Swerling 2 model is utilized when the radar target RCS is rapidly changing relative to dwelling time. It follows the Rayleigh distribution as there are no dominant radar echo.

Swerling 3 model is utilized the radar target RCS is slowly changing relative to dwelling time.  It follows the Rician distribution since there is a dominant radar echo.

Swerling 4 model is utilized the radar target RCS is rapidly changing relative to dwelling time.  It follows the Rician distribution since there is a dominant radar echo.

These models are similar to radio communication systems fading phenomena.

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Radar Ghost Target

In radar processing, ghost target appears when there is a multipath of echo signal reaching receiver.

This causes the receiver having difficulty in differentiating, identifying, and tracking the actual target.

Automotive radar experiences moving target as well as the radar equipment, which further exacerbates this ghost target vision situation and requires appropriate radar signal and data processing, in addition to front end HW.

The echo signal typically could have either Rician or Rayleigh profile for small scale fading.

In order to mitigate ghost target vision, there are 2 parameters that have to be carefully analyzed and designed, namely; pulse width and dwell timing.

These parameters are the knobs to avoid signal dispersion and time variant channel, respectively.

Obviously, understanding the multipath fading manifestation is fundamental in solving problems at hand.

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Radar Pulse Compression

As Radar technology becomes part of automotive and commercial drones, new requirements are developed to provide for this new market appropriately.

Some of the technical challenges to be addressed are stringent range and radial velocity resolution for moving target as well as radar itself.

It is well known that range resolution requires lower PRF, while radial velocity resolution requires higher PRF.

Obviously both requirements cannot be met, simultaneously.

Pulse compression technique is used to mitigate this issue.

PN pulses can be used in a way that can produce optimum resolution for both range and radial velocity.  Barker code of various lengths provides an example of PN pulses.

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Pulsed Radar Architecture

Pulsed radars are becoming more popular due to digital capability of pulse generation and detection, hence integrated circuits smaller geometry/die size, as well as enhanced range and radial velocity resolutions by appropriating designing pulse waveforms and repetitions.

The following is a typical pulse radar functional block diagram.

It should be mentioned that the electronic circuits for basic mmW radar could be as small as a smart phone.

And, for more stringent radar requirements, the overall physical size can grow to accommodate several antennas and the corresponding front ends’ HW.

Nowadays, radars are becoming part of automotive features and in few short years every autonomous car will be equipped with multiple radars.

Any advanced radar can have the capabilities to calibrate for environment in which it operates at, to reduce clutter and enhances SNR to improve radar performances.

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Radar equations, how many are there?

Radar equation relates transmit and received antenna gain, power, radar cross section, operating wavelength/frequency, range, and noise.

Consequently, radar signal to noise ratio can be computed.

There are 3 classes of radar; Search, Track, and Weather, each with its own radar equation which are used to relate physical design parameters to performance metric of a given radar.

Radar engineers use appropriate equation for designing and modeling given radar.  Search radar is utilized to scan given sky volume to find target, an obvious example is airport radar.

Tracking radar is utilized to lock onto a target and track its movement.  Whereas, Weather radar is utilized to analyze precipitations and movement of rain, snow, and/or storm.

Some important observations regarding radar equations are that Track and Weather radar equations have squared wavelength dependency, whereas Search radar does not, directly.

On the other hand, Track and Search radar equations have inverse quartic range dependency, whereas Weather radar has only inverse squared range dependency.

It should be noted that there other differences between each radar equation.

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What is Clutter?

Clutter is legacy radar terminology for background noise of target under surveillance, TUS.

Radar engineers make clear distinction between noises vs. clutter.

Noise is an unwanted signal that typically generated inherently by electronic systems, such as receiver.

Typical radio impairments are due thermal, phase error/time jitter, and quantization which are associated with noise.

Clutter on the other hand is the unwanted signal picked up by the antenna or antenna array in the radar system.

Typically, radiation pattern of antenna consists of main lobe, side lobes, and back lobe.  The main lobe is wanted whereas side lobes and back lobe are unwanted radiations.

During signal reception, the side lobes and back lobe are also picking up signal, which is not from the target under surveillance.

Since the side lobes and back lobe are much lower level below the main lobe, the unwanted signal contributions due by them are also weaker within the receiver, nevertheless  the clutter exist and needs to be quantified.

Therefore, radar systems engineers include clutter in the link budget of radar receiver.

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3D mmW Radar for Automotive

Radio Detection and Ranging, aka radar, has been used since WWII in military applications, then in Avionic, and recently entered into Automobile applications.

Automotive radar equipment are typically used for Collision Avoidance, however as Autonomous Car is becoming reality within few short years via advancement of wireless mobile communications, 5G, and connected cities, IoT, 3D mmW Radar will find its way into next generations of cars.

Originally, radar was meant to detect and provide the distance/range to the target.

Then, it evolved to provide the speed of the target using Doppler frequency shift of the Electromagnetic, EM, echo signal.

It further enhanced to estimate Time of Arrival, ToA, then Direction of Arrival, DoA, using pulsed waveform and measuring the round trip time of the echo signal.

The EM echo is created by reflection from the target.

Target effective area seen by radar is called, Radar Cross Section, RCS.  Each target has its own radar signature/RCS and can be cataloged and used for identification with advance digital signal processing of the EM echo signal, aka radar signature.

Radars are characterized either by CW or Pulsed modulation.  CW radar is better for frequency resolution of the echo, which translate to speed of the target, whereas Pulsed radar is better suited for time resolution of the echo, which translate to ToA.

3D mmW radar will provide 3 dimensional field of view of the car.

There have been handfuls of companies that make radar units for car manufacturers.

Now that the market is growing exponentially and the car radar is more than feature on high end cars, automobile manufacturers have started investing internally on radar technology design and development.

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MIMO Radar

MIMO aka Spatial Multiplexing is being used in 5G as well as WiFi technologies.

New Radars also utilize MIMO waveforms to optimize for position and velocity accuracy/resolution, simultaneously.

MIMO Radar also allows combination of Active and Passive illuminators, which can enhance the above resolutions.

MIMO relies and exploits multipath scatters and combines the received signals in a such way to optimize for SINR.

In radio communications application, there are handful of transmitted coding which are optimized per channel and predefined.

When SRS is transmitted, the receiver replies back a number which reveals the best signal coding received for that channel.

Then, the transmitter starts transmitting data with the same coding until the channel conditions are changed.

Similar algorithm can be utilized in the MIMO Pulsed Radar to enhance SINR.

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Passive Radar

Passive radar is when the EM signature pick up by the radar is not due to transmit signals by the radar itself, rather by other EM emitters such as TV station, Cellular base station, radio station, etc.

In other words, in the absence of actively sending EM signals and waiting for echo, the passive radar search for change in the EM signature in the vicinity of the passive radar and detects and perhaps identify the target of interests.

This technique requires much better receiver sensitivity to detect EM signals and process that incoming signals and compare it against bench mark signals which would have existed in the absence of the radar target in the first place.

Similar technique is used with WiFi signals in the closed area for tracking patients and elderly by Professor Dina Ketabi at MIT.

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Automotive, Short Range Radar (SRR) vs. Long Range Radar (LRR)

Physics tell us that lower frequency has longer radio range whereas higher frequency provides shorter radio range via free space loss.

Also, Physics tell higher frequency, shorter wavelength provides better spatial resolution than longer wavelength, lower frequency.

Automotive market tells us that SRR and LRR are required for a successful product.  Many automotive radar products have missed this product concept and cannot successfully capitalize on ROI.

The following table illustrates SRR vs. LRR.

If you ask these companies why haven’t design your product for both SRR and LRR, the typical response is cost concern.

The cost drove their product concept, even though there is not much market for short range or long range by itself.

This shows two fundamental conceptual product definition issue:

  1. The cost drove the definition of the product, instead of looking for a cost-effective solution which has successful ROI
  2. The definition product did not look for alternative architecture which can mitigate the cost

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Why Sphere is used to Calibrate RCS?

Radar Cross Section, RCS is the apparent cross section seen by a radar for given operating wavelength or frequency.

Needless to say, that RCS is not necessarily the physical or geometric cross section of target seen by radar.

Unit radius sphere is typically used for calibrating RCS.

Sphere scattering EM wave are isotropic.

Sphere is symmetric, consequently its RCS is independent of its aspect angle.

Sphere can be constructed for RCS measurements.

Theoretically sphere scattering performance can be accurately calculated and modeled.

All of the above make sphere an ideal RCS calibration platform.

Then, the actual target RCS can be compared to sphere RCS to account for any measurement errors.

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Drone RCS

Commercial drones are started as hobby and now find their ways in delivering vehicles and more as part of Smart City environment.

Remote drones’ navigation requires situational awareness which in turns require radar.

Consequently, these drones have to be aware of other drones and/or flying objects, and knowing RCS and drone radar signature becomes key for drones’ survivability in that environment.

At 1 cm wavelength, commercial drones have between 5 to -20 dBsm RCS depending on aspect angles and drone physical structure.

Furthermore, drones’ radar have to have some algorithms, such as clutter rejection, direction findings, and deal with multipath echo.

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FMCW vs. Pulsed Radar

Radio detection and ranging, aka radar, was invented to detect and estimate military target range before WWII, 1930’s.  Originally this was done by transmitting a Continuous radio Wave, CW or sinusoidal, and listening to the echo bouncing back from the target of interest.

The echo signal intensity would be compared to clutter, noise level of the receiver, and if above certain threshold, it would indicate the existence of the target, i.e. detection.

The bigger the target, aka radar cross section/RCS, the stronger the echo signal is.

The echo signal would also be shifted in frequency, aka as Doppler shift.  The Doppler frequency shift, frequency modulated CW/FMCW, is proportional to radial speed between radar and target.

The Doppler shift is negative relative to the CW, if the target is going away and positive if it is heading toward the radar.

During WWII, radar became extremely important and the race started to improve it by increasing the radar range that could detect a target.

This proved to be challenging as additional range meant much higher power, in fact by x4.

In other words, to double the radar range the transmitted power have to be increase by 16 times.

There were two problems, the obvious limitation of transmitted power and its security.  The stronger the transmitted power of the radar, the more obvious to be detected itself and be neutralized.

The advance of electronic technology and digital signal processing algorithms enabled optimizing the required transmitted power and acquire additional information about the target, Pulsed radar was invented.

The pulsed radar provides better time stamp of the target by compromising the frequency information/speed resolution.

Nowadays, advanced radar can provide both accurate time and frequency of the target signature with what is known as Pulse Compression Radar.

Pulsed Compression Radar modulates pulses to optimize both range and speed of the target, while maintaining the transmitted power.

Current radars can tell much more information about the target, such as; radial speed, direction, size, track, and even identify the target.

Radar has found its market in commercial application and will be important feature of autonomous car, Positive Train Control/PTC, and auto pilot airlines.

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Pulsed Radar Applications in Consumer Electronics

ORTENGA sponsored “Pulsed Radar Applications in Consumer Electronics” webinar.

ORTENGA has seasoned engineering from Autonomous Automotive, SATCOM, radar, Smart City, WiFi, and Mobile Terrestrial Radio Communications System industries in Antenna, ASIC, Algorithm, HW, FW, and SW engineering disciplines.