Compressed Sensing in Radar Signal Processing

Author:   Antonio De Maio (Universita degli Studi di Napoli 'Federico II') ,  Yonina C. Eldar (Weizmann Institute of Science, Israel) ,  Alexander M. Haimovich (New Jersey Institute of Technology)
Publisher:   Cambridge University Press
ISBN:  

9781108428293


Pages:   378
Publication Date:   17 October 2019
Format:   Hardback
Availability:   In stock   Availability explained
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Compressed Sensing in Radar Signal Processing


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Author:   Antonio De Maio (Universita degli Studi di Napoli 'Federico II') ,  Yonina C. Eldar (Weizmann Institute of Science, Israel) ,  Alexander M. Haimovich (New Jersey Institute of Technology)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 17.80cm , Height: 2.10cm , Length: 25.30cm
Weight:   0.890kg
ISBN:  

9781108428293


ISBN 10:   1108428290
Pages:   378
Publication Date:   17 October 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

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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Author Information

Antonio De Maio is a Professor in the Department of Electrical Engineering and Information Technology at the Universita degli Studi di Napoli Federico II, and a Fellow of the Institute of Electrical and Electronics Engineers (IEEE). Yonina C. Eldar is a Professor at the Weizmann Institute of Science. She has authored and edited several books, including Sampling Theory: Beyond Bandlimited Systems (Cambridge, 2015) and Compressed Sensing: Theory and Applications (Cambridge, 2012). She is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and Eurasip, and a member of the Israel National Academy of Science and Humanities. Alexander M. Haimovich is a Distinguished Professor in the Department of Electrical and Computer Engineering at the New Jersey Institute of Technology, and a Fellow of the Institute of Electrical and Electronics Engineers (IEEE).

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