题  目：Robust adaptive beamforming based on covariance matrix reconstruction and steering vector estimation
报告者：Dr. Yujie Gu
时间：10月21日（周五）下午3:20
地点：广C511会议室

Abstract
The adaptive beamformers are very sensitive to model mismatch, especially when the desired signal is present in training snapshots. In this talk, unlike previous works, we will attempt to reconstruct the interference-plus-noise covariance matrix instead of searching for the optimal diagonal loading factor for the sample covariance matrix, and then the effect of the signal is removed. Subsequently, the mismatch vector of the signal is estimated by maximizing the beamformer output power under the constraint that the corrected steering vector does not converge to any interference vector. Unlike other robust techniques, without any norm constraint either steering vector or mismatch vector is assumed in our approach. Hence, the proposed adaptive beamforming algorithm can be used even in applications where gain perturbations affect the steering vector. Simulation results demonstrate that the performance of the proposed adaptive beamformer is almost always close to the optimal value.
 
Biography
Dr. Yujie Gu received his BEng degree in Mechanical Engineering from Harbin Institute of Technology in 2001, Master degree in Control Engineering from Sichuan University in 2004, and Ph.D degree in Electronic Engineering from Zhejiang University in 2008, respectively. After graduation he joined in CETC 51 as a R&D Engineer in a new type of radar system. In 2009, he was a postdoctoral fellow in the department of Electrical and Computer Engineering at Concordia University, Canada. After that, he held a postdoctoral researcher position in School of Engineering at Bar-Ilan University, Israel. His research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada, ReSMiQ (Regroupement Stratégique en Microsystème du Québec) Postdoctoral Scholarship, and Israel Science Foundation grant. His current research interests mainly focus on statistical and array signal processing, robust adaptive beamforming, MIMO radar and MIMO communications, signal processing for radio astronomical imaging, compressive sensing and sparse reconstruction.