Book contents
- Frontmatter
- Dedication
- Contents
- List of Contributors
- Introduction
- List of 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
Introduction
Published online by Cambridge University Press: 30 September 2019
Book contents
- Frontmatter
- Dedication
- Contents
- List of Contributors
- Introduction
- List of 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
- Type
- Chapter
- Information
- Compressed Sensing in Radar Signal Processing , pp. xiv - xixPublisher: Cambridge University PressPrint publication year: 2019