Advanced sparsity-driven models and methods for radar applications

The book has 9 chapters. The following topics are dealt with: Introduction; Hybrid greedy pursuit algorithms for enhancing radar imaging quality; Two-level block sparsity model for multichannel radar signals; Parametric sparse representation for radar imaging with model uncertainty; Poisson disk sam...

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Bibliographic Details
Main Author: Li, Gang, (Author)
Format: eBook
Language: English
Published: London, United Kingdom : SciTech Publishing, 2020.
Subjects:
Doppler radar.
Imaging.
Radar.
Signal processing.
Synthetic aperture radar.
Target acquisition.
Testing.
elektronické knihy
electronic books
ISBN: 9781839530760
1839530766
9781839530753
1839530758
Physical Description: 1 online resource (viii, 254 pages) : illustrations

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Table of contents

LEADER 04832cam a2200505 i 4500
001 kn-on1230149959
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 201223t20202021enka fob 001 0 eng d
040 |a STF  |b eng  |e rda  |c STF  |d OCLCO  |d OCLCF  |d N$T  |d OCLCO  |d K6U  |d OCLCQ  |d UAB  |d UKAHL  |d CUV  |d EBLCP  |d CUS  |d OCLCL  |d UIU 
020 |a 9781839530760  |q (PDF) 
020 |a 1839530766  |q (PDF) 
020 |z 9781839530753  |q (hardback) 
020 |z 1839530758 
024 7 |a 10.1049/SBRA535E  |2 doi 
035 |a (OCoLC)1230149959  |z (OCoLC)1227387070  |z (OCoLC)1228888484 
100 1 |a Li, Gang,  |e author. 
245 1 0 |a Advanced sparsity-driven models and methods for radar applications /  |c Gang Li. 
264 1 |a London, United Kingdom :  |b SciTech Publishing,  |c 2020. 
264 4 |c ©2021 
300 |a 1 online resource (viii, 254 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a The book has 9 chapters. The following topics are dealt with: Introduction; Hybrid greedy pursuit algorithms for enhancing radar imaging quality; Two-level block sparsity model for multichannel radar signals; Parametric sparse representation for radar imaging with model uncertainty; Poisson disk sampling for high-resolution and wide-swath SAR imaging; When advanced sparse signal models meet coarsely quantized radar data; Sparsity aware micro-Doppler analysis for radar target classification; Distributed detection of sparse signals in radar networks via locally most powerful test; and Summary and perspectives. 
505 0 |a Intro -- Contents -- About the author -- Preface -- Acknowledgments -- Notation -- 1. Introduction -- 1.1 Sparsity of radar signals -- 1.2 Fundamentals of sparse signal recovery -- References -- 2. Hybrid greedy pursuit algorithms for enhancing radar imaging quality -- 2.1 Introduction -- 2.2 Radar imaging with multiple measurement vectors -- 2.3 Hybrid matching pursuit algorithm -- 2.4 Look-ahead hybrid matching pursuit algorithm -- 2.5 Conclusion -- References -- 3. Two-level block sparsity model for multichannel radar signals -- 3.1 Introduction 
505 8 |a 3.2 Formulation of the two-level block sparsity model -- 3.3 TWRI based on two-level block sparsity -- 3.4 STAP based on two-level block sparsity -- 3.5 Conclusion -- References -- 4. Parametric sparse representation for radar imaging with model uncertainty -- 4.1 Introduction -- 4.2 Parametric dictionary -- 4.3 Application to SAR refocusing of moving targets -- 4.4 Application to SAR motion compensation -- 4.5 Application to ISAR imaging of aircrafts -- 4.6 Conclusion -- References -- 5. Poisson disk sampling for high-resolution and wide-swath SAR imaging -- 5.1 Introduction 
505 8 |a 5.2 Tradeoff between high-resolution and wide-swath in SAR imaging -- 5.3 Poisson disk sampling scheme -- 5.4 SAR imaging algorithm with Poisson disk sampled data -- 5.5 Experimental results -- 5.6 Conclusion -- References -- 6. When advanced sparse signal models meet coarsely quantized radar data -- 6.1 Introduction -- 6.2 Parametric quantized iterative hard thresholding for SAR refocusing of moving targets with coarsely quantized data -- 6.3 Enhanced 1-bit radar imaging by exploiting two-level block sparsity -- 6.4 Conclusion -- References 
505 8 |a 7. Sparsity aware micro-Doppler analysis for radar target classification -- 7.1 Introduction -- 7.2 Micro-Doppler parameter estimation via PSR -- 7.3 Dynamic hand gesture recognition via Gabor-Hausdorff algorithm -- 7.4 Conclusion -- References -- 8. Distributed detection of sparse signals in radar networks via locally most powerful test -- 8.1 Introduction -- 8.2 The original LMPT detector -- 8.3 The quantized LMPT detector -- 8.4 Conclusion -- References -- 9. Summary and perspectives -- 9.1 Summary -- 9.2 Perspectives -- References -- Index 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Doppler radar. 
650 0 |a Imaging. 
650 0 |a Radar. 
650 0 |a Signal processing. 
650 0 |a Synthetic aperture radar. 
650 0 |a Target acquisition. 
650 0 |a Testing. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version  |a Li, Gang  |t Advanced sparsity-driven models and methods for radar applications  |d Edison : SciTech Publishing, 2021  |z 9781839530753  |w (OCoLC)1230929196 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpASDMMRA6/advanced-sparsity-driven?kpromoter=marc  |y Full text 

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