Compressed Sensing in Radar Signal Processing

✍ Scribed by Antonio De Maio (editor), Yonina C. Eldar (editor), Alexander M. Haimovich (editor)

• Publisher: Cambridge University Press
• Year: 2019
• Tongue: English
• Leaves: 396
• Category: Library

✦ Synopsis

Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar.

✦ Table of Contents

Cover
Front Matter
Compressed Sensing in Radar
Signal Processing
Copyright
Dedication
Contents
Contributors
Introduction
Symbols
1 Sub-Nyquist Radar: Principles
and Prototypes
2 Clutter Rejection and Adaptive
Filtering in Compressed
Sensing Radar
3 RFI Mitigation Based on Compressive
Sensing Methods for UWB
Radar Imaging
4 Compressed CFAR Techniques
5 Sparsity-Based Methods for CFAR
Target Detection in STAP
Random Arrays
6 Fast and Robust Sparsity-Based
STAP Methods for Nonhomogeneous
Clutter
7 Super-Resolution Radar Imaging
via Convex Optimization
8 Adaptive Beamforming via
Sparsity-Based Reconstruction
of Covariance Matrix
9 Spectrum Sensing for Cognitive
Radar via Model Sparsity Exploitation
10 Cooperative Spectrum Sharing
between Sparse Sensing-Based
Radar and Communication Systems
11 Compressed Sensing Methods for
Radar Imaging in the Presence of
Phase Errors and Moving Objects
Index