Speaker: Xiaolu Zeng

Affiliation: Beijing Institute of Technology

Academic title: Assistant Professor

Honorary title:  Dr.

Abstract:

Sensing in Non-Line-of-Sight (NLOS) has been greatly needed in lots of applications such as smart home, smart city, etc. In this talk, for stationary target sensing such as building structure and target-outline reconstruction, we mainly introduce ultra-wideband through-the-wall radar-based methods by jointly leveraging the intrinsic structure of the targets and the artificial intelligent image reconstruction techniques. For moving targets, we first derive the statistical model of the channel state information which turns each scattering point inside the environment into a virtual sensor so that we can leverage the reflected signal positively regardless of that it is direct path or multipath signal component. Then, we establish the link between the target motion/activity and the channel state variance which helps to decipher the surrounding activity greatly.

Biography:

Xiaolu Zeng received the B.S. degree from Harbin Institute of Technology, Harbin, China, in 2014, and the Ph.D. degree from the School of Electronic Engineering, Xidian University, Xi’an, Chin, in 2020.

He is currently an Assistant professor with the School of Information and Electronics, Beijing Institute of Technology, Beijing, China. He was a Postdoctoral Research Associate from July 2020 to December 2021, and a visiting student from September 2017 to June 2020, with the Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA. His research interests include intelligent wireless sensing, Internet of  things, and advanced driver assistance systems.