Compressed sensing in radar signal processing
Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejec...
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Cambridge University Press
2020
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| 245 | 0 | 0 | |a Compressed sensing in radar signal processing |c edited by Antonio De Maio, Yonina C. Eldar, Alexander M. Haimovich |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2020 | |
| 300 | |a 1 Online-Ressource (xxi, 357 Seiten) | ||
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| 520 | |a Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar. | ||
| 700 | 1 | |a De Maio, Antonio |d 1974- | |
| 700 | 1 | |a Eldar, Yonina C. | |
| 700 | 1 | |a Haimovich, Alexander M. |d 1954- | |
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| 912 | |a ZDB-20-CTM | ||
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| id | ZDB-20-CTM-CR9781108552653 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-18T12:04:28Z |
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| isbn | 9781108552653 |
| language | English |
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| publisher | Cambridge University Press |
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| spelling | Compressed sensing in radar signal processing edited by Antonio De Maio, Yonina C. Eldar, Alexander M. Haimovich Cambridge Cambridge University Press 2020 1 Online-Ressource (xxi, 357 Seiten) txt c cr Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar. De Maio, Antonio 1974- Eldar, Yonina C. Haimovich, Alexander M. 1954- Erscheint auch als Druck-Ausgabe 9781108428293 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/9781108552653 Volltext |
| spellingShingle | Compressed sensing in radar signal processing |
| title | Compressed sensing in radar signal processing |
| title_auth | Compressed sensing in radar signal processing |
| title_exact_search | Compressed sensing in radar signal processing |
| title_full | Compressed sensing in radar signal processing edited by Antonio De Maio, Yonina C. Eldar, Alexander M. Haimovich |
| title_fullStr | Compressed sensing in radar signal processing edited by Antonio De Maio, Yonina C. Eldar, Alexander M. Haimovich |
| title_full_unstemmed | Compressed sensing in radar signal processing edited by Antonio De Maio, Yonina C. Eldar, Alexander M. Haimovich |
| title_short | Compressed sensing in radar signal processing |
| title_sort | compressed sensing in radar signal processing |
| url | https://doi.org/10.1017/9781108552653 |
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