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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, United Kingdom :
SciTech Publishing,
2020.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 020 | |a 9781839530760 |q (PDF) | ||
| 020 | |z 9781839530753 |q (hardback) | ||
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| 049 | |a UAMI | ||
| 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. | ||
| 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 ACADEMIC - Aerospace & Radar Technology | ||
| 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. | |
| 650 | 6 | |a Radar Doppler. | |
| 650 | 6 | |a Radar. | |
| 650 | 6 | |a Traitement du signal. | |
| 650 | 6 | |a Radar à synthèse d'ouverture. | |
| 650 | 6 | |a Acquisition d'objectif. | |
| 650 | 6 | |a Essais (Technologie) | |
| 650 | 7 | |a radar. |2 aat | |
| 650 | 7 | |a testing. |2 aat | |
| 650 | 7 | |a Doppler radar |2 fast | |
| 650 | 7 | |a Radar |2 fast | |
| 650 | 7 | |a Signal processing |2 fast | |
| 650 | 7 | |a Synthetic aperture radar |2 fast | |
| 650 | 7 | |a Target acquisition |2 fast | |
| 650 | 7 | |a Testing |2 fast | |
| 650 | 7 | |a compressed sensing. |2 inspect | |
| 650 | 7 | |a Doppler radar. |2 inspect | |
| 650 | 7 | |a greedy algorithms. |2 inspect | |
| 650 | 7 | |a image classification. |2 inspect | |
| 650 | 7 | |a image coding. |2 inspect | |
| 650 | 7 | |a image enhancement. |2 inspect | |
| 650 | 7 | |a image representation. |2 inspect | |
| 650 | 7 | |a image resolution. |2 inspect | |
| 650 | 7 | |a image sampling. |2 inspect | |
| 650 | 7 | |a iterative methods. |2 inspect | |
| 650 | 7 | |a radar detection. |2 inspect | |
| 650 | 7 | |a radar imaging. |2 inspect | |
| 650 | 7 | |a radar resolution. |2 inspect | |
| 650 | 7 | |a radar target recognition. |2 inspect | |
| 650 | 7 | |a synthetic aperture radar. |2 inspect | |
| 650 | 7 | |a testing. |2 inspect | |
| 653 | |a locally most powerful test | ||
| 653 | |a radar networks | ||
| 653 | |a sparse signals distributed detection | ||
| 653 | |a radar target classification | ||
| 653 | |a sparsity aware microDoppler analysis | ||
| 653 | |a coarsely quantized radar data | ||
| 653 | |a advanced sparse signal models | ||
| 653 | |a wide-swath SAR imaging | ||
| 653 | |a high-resolution SAR imaging | ||
| 653 | |a Poisson disk sampling | ||
| 653 | |a model uncertainty | ||
| 653 | |a parametric sparse representation | ||
| 653 | |a multichannel radar signals | ||
| 653 | |a two-level block sparsity model | ||
| 653 | |a radar imaging quality enhancement | ||
| 653 | |a hybrid greedy pursuit algorithms | ||
| 653 | |a radar applications | ||
| 653 | |a advanced sparsity-driven models | ||
| 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://appknovel.uam.elogim.com/kn/resources/kpASDMMRA6/toc |z Texto completo |
| 938 | |a EBSCOhost |b EBSC |n 2706958 | ||
| 938 | |a Askews and Holts Library Services |b ASKH |n AH37504103 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL6426644 | ||
| 994 | |a 92 |b IZTAP | ||