Adaptive Radar Detection
This lecture is focused on adaptive radar detection in the presence of interference with unknown covariance matrix. After motivating the importance of the topic, the data collection process implemented in a radar system is described together with the mathematical model for the useful target and the interference component. Hence the target detection problem is formulated and some viable solutions are presented (such as for instance Kelly's Generalized Likelihood Ratio Detector, Adaptive Matched Filter (AMF), Rao test, and Wald test. Finally computational complexity and performance issues in terms of detection and false alarm probability are discussed.
Instructor
Antonio De Maio
Antonio De Maio (S'01-A'02-M'03-SM'07-F'13) was born in Sorrento, Italy, on June 20, 1974. He received the Dr.Eng. degree (with honors) and the Ph.D. degree in information engineering, both from the University of Naples Federico II, Naples, Italy, in 1998 and 2002, respectively. Currently, he is a Professor with the University of Naples Federico II. His research interest lies in the field of statistical signal processing, with emphasis on radar detection and optimization theory applied to radar signal processing. Dr. De Maio is a Fellow member of IEEE and the recipient of the 2010 IEEE Fred Nathanson Memorial Award as the young (less than 40 years of age) AESS Radar Engineer 2010 whose performance is particularly noteworthy as evidenced by contributions to the radar art over a period of several years, with the following citation for "robust CFAR detection, knowledge-based radar signal processing, and waveform design and diversity."
Publication Year: 2023