Deep Learning for Radar and Communications Automatic Target Recognition

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

This resource discusses how artificial intelligence (AI) and machine learning (ML) can be used to improve radar object detection and target recognition by analyzing the data from synthetic aperture radar (SAR) and high range resolution radar (HRR) systems. The book begins with an overview of the theory, covering the history, development and performance of AI/ML algorithms and unresolved issues. It provides real-world examples of the analysis of SAR/HRR data and communication signals. The book is practical, addressing implementation considerations when deploying AI/ML techniques, including evaluating algorithm performance and computing efficiency.

The authors bring extensive experience to the topic. Erik Blasch is a program officer at the U.S. Air Force Research Laboratory (AFRL), holds a Ph.D. in electrical engineering from Wright State University and is a Fellow of IEEE. Uttam Majumder is a senior electronics engineer at the AFRL. He holds a Ph.D. in electrical engineering from Purdue University and is a senior member of IEEE. David Garren is a professor at the Naval Postgraduate School, holds a Ph.D. from the College of William and Mary and is a senior member of IEEE.

To order this book, contact:

Artech House
US +1 800-225-9977
UK +44 (0)20 70596 8750

ISBN: 9781630816377
290 pages

Hardcover: $179
Digital Download and Online: $134