Combining Physical Optics and Method ofEquivalent Currents to Create Unique Near-Field
Propagation and Scattering Technique for
Automotive Radar Applications
Gregory Skidmore, Tarun Chawla, and Gary Bedrosian
Remcom Inc., State College, Pennsylvania, 16801, U.S.A.
IEEE COMCAS 2019
4-6 November 2019, Tel Aviv, Israel
315 S. Allen St., Suite 416 | State College, PA 16801 USA | +1.814.861.1299 phone | +1.814.861.1308 fax | sales@remcom.com | www.remcom.com | ©©Remcom
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Inc.All
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reserved.

Introduction to Auto Radar Simulation
Significant innovation is taking place in automotive industry around capabilities
for advanced driver assistance systems (ADAS)[1]-[2].
Radar sensors operating at millimeter wave bands are a key technology andrequire new modeling and simulation tools to predict their performance in driving
environments.
Simulation of radar in realistic automotive scenarios poses several challenges:• Near-field conditions that invalidate traditional RCS concepts• Densely-faceted vehicle models too complex for traditional propagation ray-tracers• Complex multipath from roadside structures (guard rails, signs, parked vehicles, etc.)• Dynamic scenarios with multiple vehicles in motion

This presentation demonstrates a new modeling and simulation capability thataddresses these challenges, combining ray-tracing and scattering simulations
from Remcom’s WaveFarer® with chirp Doppler analysis algorithms to assessradar performance for drive scenario simulations.
© Remcom Inc. All rights reserved.

Key Elements of the Solution
Physical Optics (PO) [3] for backscatter• Surface integration technique accurately predicts backscatter from highlyfaceted vehicle models in full, 4-π steradians• Does not make far-field assumptions, allowing for spherical wave incidence

Method of Equivalent Currents (MEC) [4] for edge effects• Specially derived for Remcom’s PO technique to find electric and magneticline currents• Included as line integrals to supplement PO surface integral

Geometric Optics and Uniform Theory of Diffraction (GO/UTD) [4]-[5]• Used to propagate to scattering surfaces to provide incident electric andmagnetic fields for surface integration• Used to propagate back to ensure reciprocity© Remcom Inc. All rights reserved.

Ray-tracing MethodsBasic ray-tracing approach:• Shooting and bouncing ray (SBR)
method used to find propagation paths toscattering objects (vehicles & clutter)• Augmented with algorithms to ensurethat all paths illuminate every facet of
scattering targets (critical enhancement)• Paths corrected to precise geometricpath to all integration points, maintaining
mag, phase, polarization and time ofarrival

Multipath is captured on the way toand from scattering objects.

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Field Calculations• GO/UTD: interactions with environment to compute incident fields andmultipath to/from scattering integration surfaces•

Includes multipath within scattering objects, such as corner reflectors• PO/MEC used to compute backscatter from each surface integration point•

At a high level, each facet and path to antenna has its own generalized Green’s function:− jk Ant ⋅ r
G facet,path = G(JScat , MScat ) e

where J and M are scattered electric and magnetic current densities, and the exponential
term gives phase variations on the facet surface• Total returned power is computed through complex summation of all paths(reflected, diffracted, and scattered), including phase

PRx =ΣVfacet,path

22 R Ant© Remcom Inc. All rights reserved.

Applying to Auto-Radar
Key characteristics of radar• Millimeter waves (e.g., 76-81 GHz)
• Antenna radiation patterns (far zone
assumptions reasonable)• Pulsed or chirped waveform

Ground Bounce Multipath Has
Significant Effect on Received PowerInteractions with car and environment• Near-zone scattering (vehicle is large
compared to wavelength and distance)• PO surface integration must include sphericaland diffracted wave fronts• Also phase, polarization, range dependence• Offsets for antenna arrays also critical• Multipath with ground and otherstructures both to and from targets© Remcom Inc. All rights reserved.

Drive Scenarios Modeling
Drive scenarios typically include
roadside clutter, other structures• Examples: guard rails, street sign
• Maybe buildings, walls, poles

Complex impulse response (CIR)shows mag and phase of returns
vs. time of arrival• Figure compares (a) Car alonevs. (b) car with ground & clutter• Guard rail posts & sign add large
number of secondary returns© Remcom Inc. All rights reserved.

Analysis Using Chirped Waveforms
Developed scripts and post-processingin MATLAB® [9] for range & doppler
analysis
Waveform: FMCW [8](chirpedwaveform), defined by:• Lower & upper frequency (f1, f2)• Chirp duration T• Chirp rate k=(f2-f1) / T• Optional reset time between chirps, Tr• Number of chirps/frame, NFrequency

Trf2
f1

Chirp 10T

Chirp 2 … Chirp NTime

Simulated chirp frames at several timesteps for two scenarios
Request a demonstration of WaveFarer here.
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• Adjust phases to account for transmit
frequency and time of arrival at time oftransmission for each CIR return• Generates time-sampled received
voltage waveform

Assumptions• Non-dispersion: in this study, waveform
was assumed to not change shape due
to interactions on way from Tx to Rx• Target object speeds: objects are
moving slow compared to light (eachchirp sim is a static snapshot)

Power (dBm)

Derive broadband waveform byconvolving CIRs with transmitted
waveform

Complex Impulse Response

Time of Arrival(ns)Frequency (GHz)

Derive Broadband CIR

Scattering from multiple
objects/features creates
multiple returned copiesof signal..
Time (ns)
Delays between transmitted& received copies of signal© Remcom Inc. All rights reserved.

Chirp Post-Processing
The critical simulation output is CIR (path mag & phase binned by time of arrival)
Scripts were developed in MATLAB to perform these signal processing steps
using these outputs:

1. For each path bin, phase of received signal is determined from CIR and the transmitted
chirp waveformkβ(t) =α 0 + δ + 2π f1 (t − t d ) + 2π (t − t d ) 22

2. Received signal is mixed with transmitted signal [10]; phase difference is given by

k 2β − α = δ − 2π f1 t d + 2π t d − 2π (k t d ) t2

3. Time-dependent term results in beat frequency related to range of interaction

f=k=t d k d=/s 2k r /s
beat

4. This is performed for each path, and results are combined in manner equivalent to atime-domain convolution of waveform and CIRs

DFTs are then used to determine range and Doppler (next slide)© Remcom Inc. All rights reserved.

Chirp Post-Processing (continued)
DFT of combined mixed-down signal from all paths (I&Q) provides power vs.
frequency, which can be converted to power vs. range.
DFT across chirps in a frame then determines the Doppler from path phase shifts
between chirps as the vehicles move through the scene.
Guard Rail
PostsVehicle© Remcom Inc. All rights reserved.

Scenario 1: Vehicle Braking
First scenario involved radar hostclosing on a braking vehicle• Used chirp waveform, 51 chirps / frame

Range-doppler calculated for 6 points
in time over 2.5 second duration

VehicleBraking• For each, simulated returns for 51 chirps(a single frame)

TABLE I. PARAMETERS OF BRAKING SCENARIO
Category
Chirp Waveform

Motion: HostBraking Vehicle

Parameter
Frequency
Modulation
Chirp Duration
Chirps / Frame
Velocity
Initial Velocity
Deceleration

Value
77 – 81 GHz
Sawtooth
20 us
51
20 m/s
15 m/s
4 m/s2

CLICK to see video clip
© Remcom Inc. All rights reserved.

DFTs of I&Q Determine Range-DopplerDFT of Beat Frequencies Determines
Return vs. Range

DFT across Chirps in Frame Determines
Range-Doppler

Power vs. Range at Time=0.00 sec-80-90Power (dBm)-100-110-120-130-140020406080100120

140160180200120

140160180200Frequency (MHz)Power vs. Range at Time=2.00 sec-80-90Power (dBm)-100-110-120-130-140020406080

100

Frequency (MHz)

050

100

Range (m)150

CLICK to see video clip
© Remcom Inc. All rights reserved.

Scenario 1 (Braking): Range Doppler
Results show returns from guard rail posts and vehicle at 1-second intervals• Vehicle appears at expected ranges• Relative velocity starts 5 m/s slower; decelerates to 9 m/s and 13 m/s slower as expected• Guard rails close at full velocity, but slide toward 0 and then negative as car passes them

Guard Rail
Posts

Braking
Car

Braking
Car

Braking
Car© Remcom Inc. All rights reserved.

Scenario 2: Lane Change Reveals Braking Vehicle
In 2nd scenario, braking vehicle isobstructed at firstThen blocking vehicle changes lanes,revealing braking car to radar
Scenario parameters:VehicleBraking• Obstructing vehicle matches radar hostforward velocity of 20 m/s• Changes lane along curved path to left
• All other parameters are the same asfirst scenario

CLICK to see video clip
© Remcom Inc. All rights reserved.

Scenario 2 Returns vs. Range & Range-Doppler
DFT of Beat Frequencies Determines
Return vs. Range
Power vs. Range at Time=0.00 sec

DFT across Chirps in Frame Determines
Range-Doppler-70-80-90Power (dBm)-100-110-120-130-140
0204060

80100120

140160180200120140160

180200Frequency (MHz)Power vs. Range at Time=2.00 sec-80-90Power (dBm)-100-110-120-130020406080100

Frequency (MHz)050100Range (m)150

CLICK to see video clip
© Remcom Inc. All rights reserved.

Scenario 2 (Reveal): Range Doppler
Results show returns from vehicles and clutter at 1-second intervals• Braking vehicle is obscured at start (approx. 20 dB below blocking vehicle)• Begins to emerge at 1-second point (approx. 8.5 dB down), and fully emerges by end• Relative positions, velocities, and deceleration for vehicles match expected values
Brakingcar partiallyobscured

Braking
car less
obscured

Brakingcar fully
revealed© Remcom Inc. All rights reserved.

Summary
We have presented a unique solution for predicting radar returns for automotive
radar drive scenario simulations.

• Based on Remcom’s WaveFarer®, combines ray-tracing and radar scattering methods withtechniques specifically designed to handle near-zone conditions, dense multipath, andscattering environments found in typical drive scenarios• Augmented with post-processing analysis scripts developed in MATLAB to perform rangeDoppler analysis for chirp waveforms

The methods were applied to simulate two drive scenarios for comparison.

• In both, the predicted range-Doppler results consistently match the simulated positions andvelocities of vehicles and roadside clutter.
• The second scenario demonstrated how an obstructing vehicle might reduce the ability of aradar to observe a braking car in the front.

Successful results verify ability to simulate chirp Doppler for cases relevant toautomotive radar, demonstrating a predictive simulation capability that can beused to assess concepts and alternatives during the radar design process.
© Remcom Inc. All rights reserved.

Contact Remcom
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References
1. R. Kala, On-Road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems, Butterworth-Heinemann,
2016.
2. R. Sagar, “Making Cars Safer through Technology Innovation,” Texas Instruments, June 2017,
http://www.ti.com/lit/wp/sszy009a/sszy009a.pdf.
3. A. Osipov, and S. Tretyakov, Modern Electromagnetic Scattering Theory with Applications, Chapter 8, "Method of
Physical Optics," pp. 565-633. Hoboken, New Jersey: John Wiley & Sons, 2017.
4. C. Balanis, Advanced Engineering Electromagnetics, Second Edition, pp. 326-344, 815-819, Hoboken, New Jersey:
John Wiley & Sons, 2012.
5. R. G. Kouyoumjian and P. H. Pathak, “A uniform geometrical theory of diffraction for an edge in a perfectly conducting
surface,” Proceedings of the IEEE, vol. 62, pp. 1448–1461, 1974.
6. T. S. Rappaport, Wireless Communications: Principles & Practice, New Jersey, Prentice Hall PTR, 1996.
7. M. Skolnik, Radar Handbook, Second Edition, New York: McGraw Hill, 1990.
8. C. Aydogdu, N. Garcia, L. Hammarstrand and H. Wymeersch, "Radar Communications for Combating MutualInterference of FMCW Radars," 2019 IEEE Radar Conference (RadarConf), Boston, MA, USA, 2019, pp. 1-6.
9. MATLAB® 2019a, MathWorks, Natick, Massachusetts, United States.
10. K. Ramasubramanian, "Using a complex-baseband architecture in FMCW radar systems,", Texas Instruments, May
2017, http://www.ti.com/lit/wp/spyy007/spyy007.pdf.
© Remcom Inc. All rights reserved.