Deep Learning for Radar and Communications Automatic Target Recognition

Majumder, Uttam K./ Blasch, Erik P./ Garren, David

ISBN 10: 163081637X / ISBN 13: 9781630816377

Editore: Artech House, 2020

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210 pages. 10.00x7.00x1.00 inches. In Stock. Codice articolo 163081637X

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Titolo: Deep Learning for Radar and Communications ...

Casa editrice: Artech House

Data di pubblicazione: 2020

Legatura: Hardcover

Condizione: Brand New

Descrizione articolo

Riassunto:

This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.

Informazioni sull?autore:

Erik P. Blasch is a program officer at the United States Air Force Research Laboratory (AFRL) Air Force Office of Scientific Research (AFOSR). He received Ph.D. in electrical engineering from Wright State University. He is a Fellow of IEEE. Uttam K. Majumder is a senior electronics engineer at the United States Air Force Research Laboratory (AFRL). He received his Ph.D. in electrical engineering from Purdue University. He is a senior member of IEEE. David A. Garren is a professor at the Naval Postgraduate School. He received his Ph.D. from the College of William and Mary. He is a senior member of IEEE.