A sparse recovery algorithm for DOA estimation using weighted subspace fitting

摘要

A new algorithm involving sparse recovery is proposed to address the problem of direction-of-arrival (DOA) estimation using weighted subspace fitting (WSF). The proposed algorithm proves to be a modified version of ℓ_1-SVD by using an optimal weighting matrix, wherein a scheme of regularization between sparsity penalty and subspace fitting error is also given for all SNR range. Numerical simulations verify the efficiency of the proposed algorithm and illustrate the performance improvement in low SNR.