Principles of Modern Radar: Advanced techniques
2: Georgia Tech Research Institute, Atlanta, GA, USA
This second of three volumes in the Principles of Modern Radar series offers a much-needed professional reference for practicing radar engineers. It provides the stepping stones under one cover to advanced practice with overview discussions of the most commonly used techniques for radar design, thereby bridging readers to single-topic advanced books, papers, and presentations. It spans a gamut of exciting radar capabilities from exotic waveforms to ultra-high resolution 2D and 3D imaging methods, complex adaptive interference cancellation, multi-target tracking in dense scenarios, multiple-input, multiple-output (MIMO) and much more. All of this material is presented with the same careful balance of quantitative rigor and qualitative insight of Principles of Modern Radar: Basic Principles. Each chapter is likewise authored by recognized subject experts, with the rigorous editing for consistency and suggestions of numerous volunteer reviewers from the radar community applied throughout. Advanced academic and training courses will appreciate the sets of chapter-end problems for students, as well as worked solutions for instructors. Extensive reference lists show the way for further study.
Inspec keywords: compressed sensing; radar signal processing; passive radar; array signal processing; radar interference; MIMO radar; interference suppression
Other keywords: multiinput-multioutput radar; radar techniques; radar dismount-human detection; radar waveforms; synthetic aperture radar; passive bistatic radar; compressive sensing; MIMO radar; interference mitigation techniques; array processing; radar systems; radar signal processing
Subjects: Radar equipment, systems and applications; General electrical engineering topics; Electromagnetic compatibility and interference; Signal processing and detection
- Book DOI: 10.1049/SBRA020E
- Chapter DOI: 10.1049/SBRA020E
- ISBN: 9781891121531
- e-ISBN: 9781613530245
- Format: PDF
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Front Matter
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1 Overview: Advanced Techniques in Modern Radar
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Modern radar systems are highly complex, leveraging the latest advances in technology and relying on sophisticated algorithms and processing techniques to yield exceptional products. Principals of Modern Radar is the first in a series, covering basic radar concepts, radar signal characteristics, radar subsystems, and basic radar signal processing. This text is the second in the series and contains advanced techniques, including the most recent developments in the radar community. Specifically, much of Principles of Modern Radar: Advanced Techniques discusses radar signal processing methods essential to the success of current and future radar systems. Applying these techniques may require specific hardware configurations or radar topologies, as discussed herein.
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Part I: Waveforms and Spectrum
2 Advanced Pulse Compression Waveform Modulations and Techniques
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This chapter surveys some of the more advanced pulse compression (PC) waveform modulations and techniques applied in modern radar systems, including stretch processing, stepped chirp waveforms, nonlinear frequency modulated (NLFM) waveforms, stepped frequency (SF) waveforms, quadriphase codes, and mismatched filters (MMFs) applied to phase codes. Fundamentals of phase and frequency modulated PC waveforms are covered.
3 Optimal and Adaptive MIMO Waveform Design
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This chapter develops the basic theory of optimal transmit/receive design using a multi-input, multi-output (MIMO) formulation that can account for all potential degrees of freedom (DOFs) such as waveform (fast-time), angle, and polarization. Various applications and examples are provided to further illustrate the potential impact of joint transmit/receive adaptivity.
4 MIMO Radar
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As is hopefully evident from this chapter, analysis of the utility of MIMO techniques for a particular radar application may not be straightforward. It should also be clear that transmitting orthogonal waveforms is not advantageous in every situation. The primary goal of this chapter has been to provide a framework for evaluating the appropriateness of a particular suite of MIMO waveforms for a specific radar mission. This is necessary to decide if performance will be enhanced by using a MIMO radar instead of a traditional phased array configuration.
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Part II: Synthetic Aperture Radar
5 Radar Applications of Sparse Reconstruction and Compressed Sensing
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Sparse reconstruction and design through randomization have played significant roles in the history of radar signal processing. A recent series of theoretical and algorithmic results known as compressive or compressed sensing (CS) has ignited renewed interest in applying these ideas to radar problems. A flurry of research has explored the application of CS approaches as well as closely related sparse reconstruction (SR) techniques to a wide range of radar problems. This chapter will provide some historical context for CS, describe the existing theoretical results and current research directions, highlight several key algorithms that have emerged from these investigations, and offer a few examples of the application of these ideas to radar.
6 Spotlight Synthetic Aperture Radar
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The decades of development of synthetic aperture radar (SAR) have resulted in a family of remarkable signal processing techniques that are capable of producing imagery whose cross-range resolution is independent of range and much finer than is possible to achieve with any practically-deployable real-beam antenna. SAR was initially conceived in the 1950s by Carl Wiley in the context of stripmap collection. He was, by all accounts, a talented and colorful person whose contributions include the first serious consideration of the feasibility of the solar sail. This early work ignited a legacy of research, development, and practical application that remains strong to this day.
7 Stripmap SAR
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Stripmap SAR employs a linear collection geometry and a fixed antenna orientation, typically to broadside, that is, normal to the platform velocity vector. This mode of operation achieves the finest possible cross-range resolution while surveying the passing terrain without gaps in coverage. This chapter covers the following topics: review of radar imaging concepts; Doppler beam sharpening extension; range migration algorithm; range-Doppler algorithms; and operational considerations.
8 Interferometric SAR and Coherent Exploitation
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This chapter has shown how pairs of complex SAR images can be combined to generate several useful remote sensing products. The focus has been primarily on digital elevation maps, but it has also introduced ways to measure temporal changes in the profile or reflectivity of a scene on both short and long time scales using along-track interferometry, coherent change detection, and temporal motion mapping. All of these techniques rely on measurements of interferometric phase differences between images, differing in whether and how much those images are separated along spatial and temporal baselines. Because they all rely on IPD as the fundamental measured quantity, they share many common signal processing steps: subpixel image coregistration; two-dimensional phase unwrapping or its equivalent; filtering and multilook averaging for maximizing coherence; and orthorectification and geocoding to provide useful final data products. These mission concepts and processing techniques continue to be active research areas: InSAR is expanding into true 3-D imaging using Fourier, tomographic, and other methods, while ATI is expanding into combined GMTI and SAR. More advanced SAR sensors and the advent of formation and constellation sensor systems continue to expand the menu of measurement configurations. These developments mark progress toward a capability for timely, high-quality earth resources data acquisition as well as military and security surveillance, both on a global scale.
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Part III: Array Processing and Interference Mitigation Techniques
9 Adaptive Digital Beamforming
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DBF architectures provide significant functionality enhancements for phased array radar. At the current state of digital technology, element-level DBF is often impractical for large arrays operating at high frequencies, so subarray level implementations are commonly used to reduce the digital receiver count. The choice of subarray architecture heavily impacts performance due to grating lobes and grating nulls that result from under sampling the array. Adaptive algorithms provide the ability to cancel unwanted jamming and can use low gain auxiliaries, subarrays, and high gain beams as spatial degrees of freedom; each of these work best against jamming located in specific regions of the antenna pattern.
10 Clutter Suppression Using Space-Time Adaptive Processing
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Aerospace radar systems must detect targets competing with strong clutter and jamming signals. For this reason, the radar system designer incorporates a mechanism to suppress such interference. A familiarity with the application of space-time degrees of freedom - shown herein to greatly enhance detection in interference-limited environments- is thus essential. This chapter discusses the important role of space-time adaptive processing in moving target indication radar.
11 Space-Time Coding for Active Antenna Systems
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The purpose of this chapter is to outline the main possibilities and to show that the simultaneous requirement for wideband and multiple channels opens the way to new beamforming techniques and waveforms, where different signals are simultaneously transmitted in different directions, for jointly coding space and time, and coherently processed in parallel on receive. Such concepts, first proposed and demonstrated by S. Drabowitch and J. Dorey, should now be considered as mature techniques to be implemented in operational systems.
12 Electronic Protection
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As is evident from this chapter, radar electronic warfare (EW) includes a wide range of methods by which adversary electronic attact (EA) and electronic support (ES) systems can degrade or exploit radar operation. The EA effects primarily consist of masking and deception and provide screening of targets through either support jamming or self-protection jamming deployments. Jamming is generated through either coherent or noncoherent EA system architectures: the former can preserve the phase information of the radar, the latter cannot. There are numerous EA techniques, operating in the range, Doppler, or angle dimensions of the radar, including noise, false targets, and track gate stealing. Table 12-3 lists the EA techniques mentioned briefly in this chapter, along with their intended effect, jammer type, and jammer role. There are numerous variations to forming such a list, but this provides a representative example of the diversity of EA options.
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Part IV: Post-Processing Considerations
13 Introduction to Radar Polarimetry
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Wave polarization and polarimetry play vital roles in radar target identification comprising the three phases of target detection, discrimination, and recognition. This chapter presents an introduction to radar polarimetry emphasizing the polarization behavior as described by the scattering matrix. After a brief review of linear, circular, and elliptical polarization and the geometrical parameters of polarization ellipse, such as tilt and ellipticity angles and axial ratio, Stokes parameters and scattering matrices are introduced and explained using examples on canonical targets. The projection of polarization states on the Poincare sphere is discussed. The transformation of the scattering matrix from one polarization state basis to another (e.g., linear to circular and vice versa) is derived. Unitary transformations are applied to the scattering matrix for fully polarized targets and eigen-polarization states corresponding to maximum and minimum backscattered power are derived. The location of null polarization states on the Poincare sphere is discussed, and the Huynen polarization fork is introduced as a useful tool in the visualization of optimal polarimetric parameters. Stokes reflection or Mueller matrix is derived for partially polarized waves. The distinction between Kennaugh's and Huynen's formulations of the target scattering matrix (partially polarized case) is discussed. To demonstrate the application of radar polarimetry, the scattering matrix measurements of a cone with grooves (resembling a missile reentry vehicle) are processed to extract key features such as specular scattering and edge contributions, and the usefulness of polarimetric signatures to discriminate between coated and uncoated bodies is discussed. The polarimetric behavior of precipitation clutter, sea clutter, and ground clutter is also discussed. A radar instrumentation setup for scattering matrix measurement in block diagram form is described, and implications on the setup imposed by colocation of transmit and receive antennas for monostatic measurements and the need to measure amplitude and phase of each orthogonal channel relative to a coherent source are discussed.
14 Automatic Target Recognition
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A wide variety of radar-based ATR systems and applications have been developed and documented in open literature. As different as these may seem on the surface, they all tend to revolve around four basic steps, labeled in this chapter as the unified framework for ATR. First, the target set must be identified. Then the feature set must be selected, observed, and tested to identify the targets. The most challenging parts of the problem tend to be predicting all likely target variations and discerning a feature set that sufficiently segregates the target set while being readily observable.
15 Multitarget, Multisensor Tracking
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Target tracking consists of two main steps: measurement-to-track data association and track filtering. When multiple targets are present in proximity, both steps are more prone to errors. The more the measurement covariances for multiple targets overlap, the greater the data association ambiguity. This chapter presented three sets of techniques for achieving good performance in the face of this ambiguity. One option is to incorporate features into the measurement-to-track cost matrix. This can be a reasonable approach, if the chosen feature is readily and accurately observable and if it segregates the target set. Regardless of the chosen cost function, another approach to resolving measurement-to-track ambiguity is to defer the decision until additional scans of measurements have been collected. The MHT uses this approach, which works well in cases where the ambiguity is likely to resolve overtime. In some cases, the targets may be unresolved or very closely-spaced for long periods of time, necessitating cluster tracking.
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Part V: Emerging Techniques
16 Human Detection With Radar: Dismount Detection
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This chapter provides a brief overview of current systems and development efforts, kinematic and RCS models, technical challenges, and recently proposed novel ideas relating to human detection with radar. The expected radar return for a human target was analytically derived and the most widely used human kinematic model, the Boulic-Thalmann model, was described in detail. The concept of human micro-Doppler was introduced, along with the concept of human spectrograms and the application of spectrogram analysis for classification and identification of detected targets. Key technical challenges in human detection, such as the limitations of GMTI radars, STAP processors, and Fourier-based detectors, were presented, along with a brief introduction to knowledge-aided ideas that have been proposed as a solution to some of these issues. There has been much progress in the field of human detection. However, there remains much work to be done to fully resolve questions in human modeling, kinematics, radar cross section, dismount detection, and target classification algorithm design. Advanced topics beyond the scope of this chapter but that also constitute important applications of human radar detection include the following: through-the wall detection of humans, which aims at using ultra wideband radar to detect human respiration, for important applications, such as indoor surveillance and human search and rescue of fire and earthquake victim: synthetic aperture radar detection and imaging of human targets: radar networks for border security and surveillance.
17 Advanced Processing Methods for Passive Bistatic Radar Systems
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In this chapter, after introducing the main scheme for a passive bistatic radar signal processor, advanced processing techniques have been illustrated to perform optimized detection with such sensors. In particular, the most essential steps of 2D-CCF evaluation and interference cancellation have been described in detail, showing their optimization in terms of computation resources and effectiveness. Thereafter, many specific problems related to the PBR operation were considered by providing advanced processing schemes for them and showing the results achievable against real data sets.
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Appendix A: Answers to Selected Problems
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Back Matter
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