Speaker: Xiangguang Leng, Kefeng Ji

Affiliation: College of Electronic Science and Technology, National University of Defense Technology

Academic title: Associate Professor, Professor 

Abstract:

SAR is an essential tool for maritime surveillance in all weather conditions and at night. Ships are usually affected by sea breezes and waves, generating a three-dimensional (3D) swinging motion. The ship images can thereby become severely defocused, making it extremely difficult to recognize them. However, refocusing 3D swing ships in SAR imagery is challenging with traditional approaches due to different phase errors at each scattering point on the ship. To solve this problem, a novel method for refocusing 3D swing ships in SAR imagery is proposed. The main idea is that each azimuth line of the 3D swing ship image should be modeled as a multi-component linear frequency modulation signal. The experimental results from simulated and real data show that the proposed algorithm can overcome spatial-variant defocusing of 3D swing ships. Compared with state-of-the-art algorithms, our approach reduces the image entropy by an order of magnitude. Xiangguang Leng received his Ph.D. degree in Electronic Science and Technology from National University of Defense Technology (NUDT), Changsha, China. He is currently an associate professor. His research interests mainly include remote sensing information processing, SAR image interpretation, and machine learning. 

Biography:

Dr. Leng was a recipient of the Excellent Doctoral Dissertation of Hunan Province and China Education Society of Electronics. He was also selected for a Young Elite Scientists Sponsorship Program.

Kefeng Ji received his Ph.D. degree in information and telecommunication engineering from NUDT. He is currently a professor. He has authored or coauthored over 80 papers. His current research interests include signal processing, machine learning, pattern recognition, remote sensing information processing, SAR image interpretation, and marine surveillance.