Angle estimation for bistatic MIMO radar with unknown mutual coupling based on three-way compressive sensing  

作　　者：Xinhai Wang Gong Zhang Fangqing Wen De Ben Wenbo Liu 

机构地区：[1]Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education,Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China [2]Electronic and Information School, Yangtz University, Jingzhou 434023, China [3]College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

出　　处：《Journal of Systems Engineering and Electronics》2017年第2期257-266,共10页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61071163;61071164;61471191;61501233);the Fundamental Research Funds for the Central Universities(NP2014504);the Aeronautical Science Foundation(20152052026);the Electronic & Information School of Yangtze University Innovation Foundation(2016-DXCX-05);the Priority Academic Program Development of Jiangsu Higher Education Institutions

摘　　要：The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions. © 2017 Beijing Institute of Aerospace Information.The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions. © 2017 Beijing Institute of Aerospace Information.

关 键 词：Channel estimation Codes (symbols) Compressed sensing Cramer Rao bounds Feedback control MIMO radar MIMO systems Radar Radar signal processing Signal reconstruction Singular value decomposition Telecommunication repeaters TENSORS 

分 类 号：TN958[电子电信—信号与信息处理]