Reweighted Regularized Sparse Recovery for DOA Estimation With Unknown Mutual Coupling

Abstract

In this letter, the direction-of-arrival (DOA) estimation of uniform linear array under unknown mutual coupling is dealt with by proposing a reweighted regularized sparse recovery algorithm. The proposed method first formulates a block-sparse representation model without mutual coupling compensation and array aperture loss. Then, a reweighted l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm minimization scheme is formulated to recover the block-sparse matrix, in which a weighted matrix is designed with a novel MUSIC-Like spectrum function for enhancing the sparsity of solution. Finally, the spatial spectrum of the recovered matrix is utilized to estimate DOAs. Due to using the whole array aperture and enhanced sparsity of solution, the proposed method can achieve superior performance than the existing regularized sparse recovery methods. Some simulation results are carried out to demonstrate the superiority of the proposed method.