Sparse Representations for Radar with MATLAB Examples

Peter Knee

ISBN 10: 3031003918 / ISBN 13: 9783031003912

Published by Springer International Publishing, 2012

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar.

Seller Inventory # 9783031003912

Bibliographic Details

• Title: Sparse Representations for Radar with MATLAB Examples
• Publisher: Springer International Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3031003918
• ISBN 13: 9783031003912
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 191H x 6D millimeters 235 millimeters width by 191 millimeters height by 6 millimeters depth
• Weight: 183 grams

About this title

Synopsis

Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar

About the Author

Peter A. Knee received a B.S. (with honors) in electrical engineering from the University of New Mexico, Albuquerque, New Mexico, in 2006, and an M.S. degree in electrical engineering from Arizona State University in 2010. While at Arizona State University, his research included the analysis of high-dimensional Synthetic Aperture Radar (SAR) imagery for use with Automatic Target Recognition (ATR) systems as well as dictionary learning and data classification using sparse representations. He is currently an employee at Sandia National Laboratories in Albuquerque, New Mexico, focusing on SAR image analysis and software defined radios