MIMO Radar Signal Processing (IEEE Press)
The first book to present a systematic and coherent picture of MIMO radars
Due to its potential to improve target detection and discrimination capability, Multiple-Input and Multiple-Output (MIMO) radar has generated significant attention and widespread interest in academia, industry, government labs, and funding agencies. This important new work fills the need for a comprehensive treatment of this emerging field.
Edited and authored by leading researchers in the field of MIMO radar research, this book introduces recent developments in the area of MIMO radar to stimulate new concepts, theories, and applications of the topic, and to foster further cross-fertilization of ideas with MIMO communications. Topical coverage includes:
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Adaptive MIMO radar
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Beampattern analysis and optimization for MIMO radar
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MIMO radar for target detection, parameter estimation, tracking,association, and recognition
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MIMO radar prototypes and measurements
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Space-time codes for MIMO radar
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Statistical MIMO radar
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Waveform design for MIMO radar
Written in an easy-to-follow tutorial style, MIMO Radar Signal Processing serves as an excellent course book for graduate students and a valuable reference for researchers in academia and industry.
Why Read This Book
You will get the first coherent, research-grounded treatment of MIMO radar that connects theory, algorithms, and practical signal-processing techniques; the book synthesizes contributions from leading researchers so you can see both foundational results and cutting-edge approaches. You will learn how MIMO concepts improve detection, resolution, and parameter estimation, and gain the analytical tools to design and evaluate MIMO radar systems for real applications.
Who Will Benefit
Graduate students, radar/defense engineers, and DSP researchers who need a rigorous, application-focused introduction to MIMO radar theory, waveform design, and adaptive signal processing for target detection and parameter estimation.
Level: Advanced — Prerequisites: Linear algebra, probability and stochastic processes, classical signal processing (Fourier, sampling, filtering), basic radar concepts (pulse radar, matched filtering), and familiarity with complex baseband notation; familiarity with MATLAB or numerical computing is highly recommended.
Key Takeaways
- Understand the fundamental principles of MIMO radar including virtual arrays, waveform diversity, and spatial-temporal degrees of freedom
- Design and evaluate transmit waveforms and antenna configurations to improve target detection and resolution
- Analyze estimation and detection performance using tools such as the Cramér–Rao bound and likelihood-based detectors
- Implement advanced array processing algorithms (DOA estimation, beamforming, space-time adaptive processing) tailored to MIMO architectures
- Apply adaptive MIMO processing techniques to mitigate clutter, interference, and multipath and to enhance target discrimination
- Relate MIMO radar concepts to MIMO communications to exploit cross-disciplinary techniques (e.g., waveform diversity, coding)
Topics Covered
- Overview of MIMO Radar: Motivation and Historical Context
- Signal Models for MIMO Radars and Virtual Array Concepts
- Waveform Design and Transmit Diversity for MIMO Systems
- Array Processing and Beamforming in MIMO Radar
- Direction-of-Arrival (DOA) and Parameter Estimation Techniques
- Detection Theory and Performance Analysis for MIMO Radar
- Cramér–Rao Bounds and Statistical Performance Limits
- Adaptive MIMO Radar and Space–Time Adaptive Processing (STAP)
- Clutter, Multipath, and Interference Mitigation
- MIMO SAR and Imaging Applications
- Connections Between MIMO Radar and MIMO Communications
- Practical Implementation Issues and Simulation Examples
- Emerging Topics: Compressed Sensing, Wavelets, and Future Directions
Languages, Platforms & Tools
How It Compares
Compared with Mark Richards' 'Fundamentals of Radar Signal Processing' (which gives a broad radar DSP foundation), Jian Li's book zeroes in on MIMO-specific theory and algorithms; it also complements classic array-processing texts (e.g., Johnson & Dudgeon) by focusing on waveform diversity and MIMO performance analysis.
