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A sparse recovery algorithm for DOA estimation using weighted subspace fitting
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DOI：10.1016/j.sigpro.2012.03.020.png)
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Abstract
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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. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Direction-of-arrival
Weighted subspace fitting
Sparse recovery
Second-order cone programming
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