Sparse Array Signal Processing

来源: 信誉好的网投老平台 发布时间:2024-01-09 点击: Views






This talk will detail two approaches for direction-of-arrival (DOA) estimation or beamforming in array signal processing from the perspective of sparsity. In the first part of this talk, we consider an array model in which a small number of sensors are distorted by unknown sensor gain and phase uncertainties. With such an array model, the problem of joint DOA estimation and distorted sensor detection is formulated under the framework of low-rank and row-sparse decomposition. We derive an iteratively reweighted least squares algorithm to solve the resulting problem. In the second part of this talk, we consider the sparse array beamformer design problem and devise an algorithm for adaptive beamforming. Our strategy is based on finding a sparse beamformer weight to maximize the output signal-to-interference-plus-noise ratio. The proposed method utilizes alternating direction method of multipliers (ADMM), and admits closed-form solutions at each ADMM iteration.


Dr. Huang currently is a postdoctoral researcher at Chalmers University of Technology in Sweden. Huiping received his M.Sc. and Ph.D. degrees from Shenzhen University and TU Darmstadt, respectively, both in Electrical and Electronic Engineering. He was a visiting student at Southern University of Science and Technology in 2018, a visiting Ph.D. student at the University of Luxembourg in 2022, and a visiting scholar at Lund University in 2023. His research interests lie in optimization and compressive sensing theory and their applications to signal processing and wireless communications, with main focuses on direction-of-arrival estimation, channel estimation, robust adaptive beamforming, sparse array design, dual-function radar and communications, etc. Huiping is serving as a technical reviewer for several peer-reviewed journals and conferences, including but not limited to IEEE TSP, IEEE TAES, IEEE JSAC, IEEE SPL, IEEE WCL, Signal Processing (Elsevier), Digital Signal Processing (Elsevier), Digital Signal Processing (Elsevier), IEEE ICASSP, IEEE SAM, IEEE ICC, and Globecom.