Speaker: Guolong Cui

Affiliation: University of Electronic Science and Technology of China

Academic title: Professor

Honorary title: Young Changjiang scholar

Abstract:

Mainlobe jamming is always a hot and difficult problem in radar detection field. Cognitive radar can make use of prior information to adaptively adjust multi-dimensional parameters such as transmission, reception, and processing, which greatly improves interference suppression ability. Aiming at the problem of multi-mainlobe jamming suppression, this report introduces the design and processing methods of cognitive radar waveform resorting to multi-domain cooperation. Through the design of multi-domain parameters such as waveform space-time frequency and echo multi-domain processing, jamming suppression and separation are realized, and the signal-to-noise ratio of radar target echo is improved. The report finally introduces the future direction of anti-mainlobe jamming technology.

Biography:

Guolong Cui  received the B.S. degree in electronic information engineering and the M.S. and Ph.D. degrees in signal and information processing from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2005, 2008, and 2012, respectively. From January 2011 to April 2011, he was a Visiting Researcher with the University of Naples Federico II, Naples, Italy. From June 2012 to August 2013, he was a Post-Doctoral Researcher with the Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA. From September 2013 to July 2018, he was an Associate Professor with UESTC, where he has been a Professor since August 2018. His research interests include cognitive radar, array signal processing, multiple-input– multiple-output (MIMO) radar, and through-the-wall radar.