Automotive radars, along with other sensors such as lidar, (which stands for "light detection and ranging"), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter-wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird's-eye view to the existing research community.

Automotive Radars: A review of signal processing techniques

I. Parallelism 1. Introduction 2. Parallel Computer Architectures 3. Parallel Programming Considerations II. Applications 4. General Application Issues 5. Parallel Computing in CFD 6. Parallel Computing in Environment and Energy 7. Parallel Computational Chemistry 8. Application Overviews III. Software technologies 9. Software Technologies 10. Message Passing and Threads 11. Parallel I/O 12. Languages and Compilers 13. Parallel Object-Oriented Libraries 14. Problem-Solving Environments 15. Tools for Performance Tuning and Debugging 16. The 2-D Poisson Problem IV. Enabling Technologies and Algorithms 17. Reusable Software and Algorithms 18. Graph Partitioning for Scientific Simulations 19. Mesh Generation 20. Templates and Numerical Linear Algebra 21. Software for the Scalable Solutions of PDEs 22. Parallel Continuous Optimization 23. Path Following in Scientific Computing 24. Automatic Differentiation V. Conclusion 25. Wrap-up and Features

Sourcebook of parallel computing

Two-dimensional (2-D) inverse synthetic aperture radar (ISAR) imaging has been widely used in target scattering diagnosis, modeling and target identification. A major shortcoming is that a 2-D ISAR image cannot provide information on the relative altitude of each scattering center on the target. In this paper, we present an interferometric inverse synthetic aperture radar (IF-ISAR) image processing technique for three-dimensional (3-D) target altitude image formation. The 2-D ISAR images are obtained from the signature data acquired as a function of frequency and azimuthal angle. A 3-D IF-ISAR altitude image can then be derived from two 2-D images reconstructed from the measurements by antennas at different altitudes. 3-D altitude image formation examples from both indoor and outdoor test range data are demonstrated on complex radar targets.

Three-dimensional interferometric ISAR imaging for target scattering diagnosis and modeling

This paper develops three-dimensional (3D), bistatic parametric models that describe canonical radar scattering responses of several geometric objects. These models find use in inverse scattering-based processing of high-frequency radar returns. Canonical feature models are useful for extracting geometry from synthetic-aperture radar (SAR) scattering measurements and as feature primitives for automatic target recognition (ATR) and scene visualization. Previous work has considered monostatic feature models for two-dimensional (2D) radar processing; we extend this work to consider bistatic and 3D radar apertures. In the work presented here, we generalize geometric theory of diffraction (GTD) solutions for several scattering mechanisms in a plane. Products of these planar mechanisms in azimuth and elevation are used to produce 3D bistatic scattering models for six canonical shapes: a rectangular plate, dihedral, trihedral, cylinder, top-hat, and sphere. The derived models are characterized by a small number of parameters, and are shown to agree with results obtained from high-frequency, asymptotic scattering simulations.

Canonical Scattering Feature Models for 3D and Bistatic SAR

The optimisation of the transmission radar pulse shape to maximise either target detection or identity discrimination between the T-72 and M1 main battle tanks is investigated. Significant performance improvements in target detection and identification are obtained using such matched illumination transmission waveforms over that of standard chirped pulses.

Enhanced target detection and identification via optimised radar transmission pulse shape

Xpatch, developed at SAIC-DEMACO under the leadership of the Air Force Research Laboratory (AFRL), has become the premier high frequency simulation code suite for radar signature predictions. Xpatch applies the shooting and bouncing ray (SBR) method to realistic 3D targets in order to generate 0D through 3D radar signatures. The Xpatch prediction codes and analysis tools for measured and predicted radar cross section (RCS), high resolution range profile (HRR), and synthetic aperture radar (SAR) imagery are unparalleled in accuracy and speed across industry and the government. The Xpatch toolset is the basis for multiple DoD programs and is used by over 420 organizations across the USA.

Xpatch 4: the next generation in high frequency electromagnetic modeling and simulation software

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time domain signatures, and synthetic aperture radar (SAR) images of realistic 3-D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, curved surfaces, or solid geometries. The computer code, XPATCH, based on the shooting and bouncing ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. XPATCH computes the first-bounce physical optics plus the physical theory of diffraction contributions and the multi-bounce ray contributions for complex vehicles with materials. It has been found that the multi-bounce contributions are crucial for many aspect angles of all classes of vehicles. Without the multi-bounce calculations, the radar return is typically 10 to 15 dB too low. Examples of predicted range profiles, SAR imagery, and radar cross sections (RCS) for several different geometries are compared with measured data to demonstrate the quality of the predictions. The comparisons are from the UHF through the Ka frequency ranges. Recent enhancements to XPATCH for MMW applications and target Doppler predictions are also presented.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.

Xpatch prediction improvements to support multiple ATR applications

This paper describes a methodology of modeling 3D SAR images using ray-based high frequency electromagnetic (EM) techniques. Various ray-based EM techniques have been developed in the past for 2D SAR simulations (R. Bhalla and H. Ling, 1995). This work will extend on those approaches for modeling 3D SAR images.

A fast algorithm for 3D SAR simulation of target and terrain using Xpatch

Synthetic Aperture Radar (SAR) image modeling tools are of high interest to Automatic Target Recognition algorithm evaluation because they allow the testing of ATR's over a wide range of extended operating conditions (EOCs). Typically, extended operating conditions include target aspect, target configuration, target obscuration, and background terrain variations. This paper discusses enhancements to the legacy XpatchES model and the development of a new integrated SAR prediction toolset for targets in realistic 3-D terrain settings. The prediction toolset includes 2-D and 3-D visual target configuration and scene layout capabilities, a terrain elevation profile interface, and scattering center based on- line target prediction. The toolset allows the insertion of synthetic target chips into both measured and synthetic background models. For the synthetic background case a 3-D terrain model is used to accurately compute local slope, shadowing and layover effects. Additionally, natural clutter returns are modeled from a statistical database derived from measured data. Model enhancements and sample imagery are presented.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Dennis J. Andersh

Papers

Xpatch 4: the next generation in high frequency electromagnetic modeling and simulation software

XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays

Xpatch prediction improvements to support multiple ATR applications

A fast algorithm for 3D SAR simulation of target and terrain using Xpatch

Development of SAR scene modeling tools for ATR performance evaluation