Speaker: Xue Jiang

Affiliation: Shanghai Jiao Tong University

Academic title: Professor

Honorary title: IEEE senior member, the Excellent Young Scientists Fund from National Natural Science Foundation of China

Abstract:

Beamforming is a spatial filtering technique using a sensor array to enhance the desired signal and suppress interferences and noise. Most existing beamforming approaches are based on the minimum variance (MV) criterion which is statistically optimal only for Gaussian signals. However, real-world signals often exhibit non-Gaussianity. Many digitally modulated signals arising in radar, sonar and wireless communications are demonstrated to be sub-Gaussian. In this case, the higher-order statistics, which contain useful statistical information, can be utilized to improve the performance of the beamformer. A robust beamforming by infinity-norm minimization has been proposed, which demonstrates its optimality by implicitly utilizing the higher-order statistics. We make use of a new definition of the Lp-norm of a complex-valued vector. The resulting optimization problem is cast as a linear programming and hence can be solved efficiently. To further reduce the computational complexity, an alternating direction method of multipliers (ADMM) has been proposed, which is well-suited for large-scale problems. Simulation results demonstrate the superiority of the proposed infinity-norm based robust beamforming over several state-of-the-art robust beamformers and show that its performance can approach the optimal performance bounds.

Biography:

Xue Jiang (Senior Member, IEEE) received the Ph.D. degree in electrical engineering from McMaster University, Hamilton, ON, Canada, in 2014. She held the Postdoctoral Fellow position with McMaster University, in 2014-2015, and Arizona State University, Tempe, AZ, USA, in 2015-2016. In 2016, she joined the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China, where she is currently a Professor. Her research interests include array processing, target recognition, image processing, data science and numerical optimization, with applications to radar and remote sensing. Dr. Jiang was one of the finalists of the Best Student Paper Award of the IEEE 2013 Radar Conference. She was an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING and serves as the Editorial Board Member for IET Radar, Sonar & Navigation. She is a recipient of the Excellent Young Scientists Fund from National Natural Science Foundation of China.