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Real-Valued Reweighted l1 Norm Minimization Method Based on Data Reconstruction in MIMO Radar
Qi LIU Wei WANG Dong LIANG Xianpeng WANG
IEICE TRANSACTIONS on Communications
Publication Date: 2015/11/01
Online ISSN: 1745-1345
Type of Manuscript: PAPER
Category: Antennas and Propagation
MIMO radar, DOA estimation, sparse representation, real-valued reweighted l1 norm minimization,
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In this paper, a real-valued reweighted l1 norm minimization method based on data reconstruction in monostatic multiple-input multiple-output (MIMO) radar is proposed. Exploiting the special structure of the received data, and through the received data reconstruction approach and unitary transformation technique, a one-dimensional real-valued received data matrix can be obtained for recovering the sparse signal. Then a weight matrix based on real-valued MUSIC spectrum is designed for reweighting l1 norm minimization to enhance the sparsity of solution. Finally, the DOA can be estimated by finding the non-zero rows in the recovered matrix. Compared with traditional l1 norm-based minimization methods, the proposed method provides better angle estimation performance. Simulation results are presented to verify the effectiveness and advantage of the proposed method.