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• W2956166052 abstract "Abstract With the development of massive multiple-input mutiple-output (MIMO) technique, high-resolution direction-of-arrival (DOA) estimation has attracted great attention. A novel sparse signal reconstruction method based on the inherent block rank sparsity of the sub-matrix is proposed for high resolution DOA estimation with large-scale arrays under the condition of unknown mutual coupling. In the proposed method, by taking advantage of the banded symmetric Toeplitz structure of the mutual coupling matrix (MCM), a novel block representation model is firstly formulated by parameterizing the steering vector. Then, exploiting the inherent block sparsity characteristics of the sub-matrix, a reweighted nuclear norm minimization algorithm is proposed to reconstruct the sparse matrix, in which the weighted matrix is designed by using the spectrum of MUSIC-Like algorithm. Finally, the DOAs are achieved by searching the non-zeros blocks of the recovered matrix. The proposed method not only makes full use of the block rank sparsity characteristics of the sub-matrix and weighted matrix for enhancing the sparse solution, but also avoids the array aperture loss. Thus, the proposed method has superior estimation performance than the state-of-the-art algorithms under the condition of unknown mutual coupling. Especially, in the case of large-scale antennas, the advantage of the proposed method is more obvious. Some computer simulation results are performed to verify the advantage of our proposed method." @default.
• W2956166052 created "2019-07-23" @default.
• W2956166052 creator A5002971389 @default.
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• W2956166052 date "2019-11-01" @default.
• W2956166052 modified "2023-10-16" @default.
• W2956166052 title "Block rank sparsity-aware DOA estimation with large-scale arrays in the presence of unknown mutual coupling" @default.
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• W2956166052 doi "https://doi.org/10.1016/j.dsp.2019.06.013" @default.
• W2956166052 hasPublicationYear "2019" @default.
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