Provides broad and accessible coverage of the latest theoretical and practical advances in radar signal processing using tools from compressive sensing, including clutter rejection, CFAR detection, and adaptive beamforming. It is ideal for researchers, graduate students and industry professionals working in signal processing and radar.
Provides broad and accessible coverage of the latest theoretical and practical advances in radar signal processing using tools from compressive sensing, including clutter rejection, CFAR detection, and adaptive beamforming. It is ideal for researchers, graduate students and industry professionals working in signal processing and radar.
Preface Antonio De Maio, Yonina C. Eldar and Alexander M. Haimovich; 1. Sub-Nyquist radar: principles and prototypes Kumar Vijay Mishra and Yonina C. Eldar; 2. Clutter rejection and adaptive filtering in compressed sensing radar Peter B. Tuuk; 3. RFI mitigation based on compressive sensing methods for UWB radar imaging Tianyi Zhang, Jiaying Ren, Jian Li, David J. Greene, Jeremy A. Johnston and Lam H. Nguyen; 4. Compressed CFAR techniques Laura Anitori and Arian Maleki; 5. Sparsity-based methods for CFAR target detection in STAP random arrays Haley H. Kim and Alexander M. Haimovich; 6. Fast and robust sparsity-based STAP method for nonhomogeneous clutter Xiaopeng Yang, Yuze Sun, Xuchen Wu, Teng Long and Tapan K. Sarkar; 7. Super-resolution radar imaging via convex optimization Reinhard Heckel; 8. Adaptive beamforming via sparsity-based reconstruction of covariance matrix Yujie Gu, Nathan A. Goodman and Yimin D. Zhang; 9. Spectrum sensing for cognitive radar via model sparsity exploitation Augusto Aubry, Vincenzo Carotenuto, Antonio De Maio and Mark Govoni; 10. Cooperative spectrum sharing between sparse-sensing-based radar and communication systems Bo Li and Athina P. Petropulu; 11. Compressed sensing methods for radar imaging in the presence of phase errors and moving objects Ahmed Shaharyar Khwaja, Naime Ozben Onhon and Mujdat Cetin.
Preface Antonio De Maio, Yonina C. Eldar and Alexander M. Haimovich; 1. Sub-Nyquist radar: principles and prototypes Kumar Vijay Mishra and Yonina C. Eldar; 2. Clutter rejection and adaptive filtering in compressed sensing radar Peter B. Tuuk; 3. RFI mitigation based on compressive sensing methods for UWB radar imaging Tianyi Zhang, Jiaying Ren, Jian Li, David J. Greene, Jeremy A. Johnston and Lam H. Nguyen; 4. Compressed CFAR techniques Laura Anitori and Arian Maleki; 5. Sparsity-based methods for CFAR target detection in STAP random arrays Haley H. Kim and Alexander M. Haimovich; 6. Fast and robust sparsity-based STAP method for nonhomogeneous clutter Xiaopeng Yang, Yuze Sun, Xuchen Wu, Teng Long and Tapan K. Sarkar; 7. Super-resolution radar imaging via convex optimization Reinhard Heckel; 8. Adaptive beamforming via sparsity-based reconstruction of covariance matrix Yujie Gu, Nathan A. Goodman and Yimin D. Zhang; 9. Spectrum sensing for cognitive radar via model sparsity exploitation Augusto Aubry, Vincenzo Carotenuto, Antonio De Maio and Mark Govoni; 10. Cooperative spectrum sharing between sparse-sensing-based radar and communication systems Bo Li and Athina P. Petropulu; 11. Compressed sensing methods for radar imaging in the presence of phase errors and moving objects Ahmed Shaharyar Khwaja, Naime Ozben Onhon and Mujdat Cetin.
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