Details
Advances in Adaptive Radar Detection and Range Estimation
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149,79 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 03.12.2021 |
| ISBN/EAN: | 9789811663994 |
| Sprache: | englisch |
| Anzahl Seiten: | 218 |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<div><div>This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.</div><div>In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.</div><div>Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.</div></div><div><br></div>
<div>Introduction.- Adaptive Radar Detection: Classical Approach.- Knowledge-Aided Detectors.- Detectors with Range Estimation Capabilities.- Knowledge-Aided Detectors with Enhanced Range Estimation Capabilities.- Conclusions.</div><div><br></div>
<div><div><div>1. Chengpeng Hao</div><div>He is currently a professor at the Institute of Acoustics, Chinese Academy of Sciences (CAS). His research interests are in the fields of statistical signal processing, array signal processing, and radar/sonar engineering. He is an author or coauthor of more than 100 scientific publications in international journals and conferences. His research has earned him a number of awards, including the Outstanding Achievement Honor in Science from CAS and the Chinese State Advanced Science and Technique Second Prize. He is a senior member of IEEE. He currently serves as Associate Editors for IEEE Access, EURASIP Journal on Advances in Signal Processing (Springer) and Signal, Image and Video Processing (Springer).</div><div><br></div><div>2. Danilo Orlando</div><div>He is currently a professor at Universitàdeglistudi Niccolò Cusano. His main research interests are in the field of statistical signal processing with radar/sonar applications. He is an author or coauthor of more than 60 scientific publications in international journals and conferences. He is a senior member of IEEE. He is currently a senior area editor for IEEE Transactions on Signal Processing and an Associate Editor for EURASIP Journal on Advances in Signal Processing (Springer).</div><div><br></div><div>3. Jun Liu</div><div>He is currently an Associate Professor at the University of Science and Technology of China. His main research interests include statistical signal processing, machine learning, and image processing. He is an author or coauthor of more than 80 scientific publications in international journals. He is a senior member of IEEE. He currently serves as Associate Editors for Signal Processing (Elsevier) and IEEE Signal Processing Letters.</div><div><br></div><div>4. Chaoran Yin</div><div>He is currently a Ph.D student at School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, and Institute of Acoustics, Chinese Academy of Sciences. He received his B.E. degree of Electromagnetic fields and wireless technology at Northwestern Polytechnical University, Shaanxi, China, in 2018. His main field of interest is signal and information processing, especially statistical signal processing.</div></div></div>
<div><div><div>This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.</div><div>In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.</div><div>Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.</div></div></div><div><br></div>
<p>Provides a comprehensive and systematic framework about the design of adaptive architectures</p><p>Presents an extensive number of illustrative examples based upon both simulated and real-recorded data</p><p>Valuable resources for readers working on statistical signal processing and its applications to radar systems</p>
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