Principles and Applications of Relax: A Robust and Universal Estimator - Rilegato

Wu, Renbiao; Jia, Qiongqiong; Yang, Lei; Feng, Qing

Rilegato

ISBN 10: 9811369313 ISBN 13: 9789811369315

Casa editrice: Springer Nature, 2019

Riassunto

The multiple signal demixing and parameter estimation problems that result from the impacts of background noise and interference are issues that are frequently encountered in the fields of radar, sonar, communications, and navigation. Research in the signal processing and control fields has always focused on improving the estimation performance of parameter estimation methods at low SNR and maintaining the robustness of estimations in the presence of model errors. This book presents a universal and robust relaxation estimation method (RELAX), and introduces its basic principles and applications in the fields of classical line spectrum estimation, time of delay estimation, DOA estimation, and radar target imaging. This information is explained comprehensively and in great detail, and uses metaphors pertaining to romantic relationships to visualize the basic problems of parameter estimation, the basic principles of the five types of classical parameter estimation methods, and the relationships between these principles. The book serves as a reference for scientists and technologists in the fields of signal processing and control, while also providing relevant information for graduate students in the related fields.

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Informazioni sull?autore

Renbiao Wu is the Tianjin Professor and the Director of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. He received his B.Sc. and M.Sc. in Electrical Engineering from the Northwest Polytechnic University in 1988 and 1991 respectively, and his Ph.D. in Electrical Engineering from Xidian University in 1994. He has worked at the Imperial College of London, the University of Florida, and Virginia Tech as a Distinguished Research Scholar, Visiting Professor, and Postdoctoral Fellow for 5 years. His research interests include adaptive array signal processing and spectral estimation, especially in regards to their applications in GNSS and radar. He has published over 300 peer-reviewed papers, and ten plus books and book chapters. He is the recipient of the Chinese National Outstanding Young Investigator Award in 2003.

Qiongqiong Jia is a lecturer of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. She received her B.Sc. and M.Sc. from the Civil Aviation University of China in 2008 and 2011, and her specialized master degree in navigation engineering from ENAC in France in 2015. Her research interests include adaptive array signal processing and spectral estimation regarding their applications to GNSS. She has published 20 papers, and co-authored three books and book chapters.

Lei Yang is currently an associate professor of Tianjin Key Lab for Advanced Signal Processing at Civil Aviation University of China. He received his B. Sc. and Ph. D. degrees all from Xidian University, Xi'an, China in Electronic Engineering and Signal and Information Processing, respectively. He has worked at School of Eletrical and Electronic Engineering of Nanyang Technology University (NTU), Singapore and Temasek Lab@NTU, Singapore, as a full-time (postdoctoral) research fellow and research scientist, respectively, for 4 years. His research interests include radar imaging for stationary scene and moving targets. He has published over 40 academic papers that are all indexed by SCI and EI database. He is now with the Recruitment Programme of Global Experts (the Thousand Young Talents Plan) of Tianjin, China.

Qing Feng is a lecturer of the Tianjin Key Lab for Advanced Signal Processing at the Civil Aviation University of China. She received her M.Sc. from the Civil Aviation University of China in 2005. Her research interests include adaptive array signal processing and spectral estimation, especially in regards to their applications in radar. She has published 8 papers, and co-authored two books.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2019
• Lingua: Inglese
• ISBN 10: 9811369313
• ISBN 13: 9789811369315
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 320
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania