%0 Journal Article
%T Computationally Efficient Compressed Sensing-Based Method via FG Nystr£¿m in Bistatic MIMO Radar with Array Gain-Phase Error Effect
%A Baidoo
%A Evans
%A Hu
%A Jurong
%A Tian
%A Ying
%A Zhan
%A Lei
%J -
%D 2020
%R https://doi.org/10.1155/2020/1586353
%X In this paper, a robust angle estimator for uncorrelated targets that employs a compressed sense (CS) scheme following a fast greedy (FG) computation is proposed to achieve improved computational efficiency and performance for the bistatic MIMO radar with unknown gain-phase errors. The algorithm initially avoids the wholly computation of the received signal by compiling a lower approximation through a greedy Nystr£¿m approach. Then, the approximated signal is transformed into a sparse signal representation where the sparsity of the target is exploited in the spatial domain. Finally, a CS method, Simultaneous Orthogonal Matching Pursuit with an inherent gradient descent method, is utilized to reconstruct the signal and estimate the angles and the unknown gain-phase errors. The proposed algorithm, aside achieving closed-form resolution for automatically paired angle estimation, offers attractive computational competitiveness, specifically in large array scenarios. Additionally, the analyses of the computational complexity and the Cram¨¦r¨CRao bounds for angle estimation are derived theoretically. Numerical experiments demonstrate the improvement and effectiveness of the proposed method against existing methods
%U https://www.hindawi.com/journals/ijap/2020/1586353/