稀疏阵列的鲁棒矩阵填充DOA估计算法

doi:10.12305/j.issn.1001-506X.2024.05.02

Abstract

Abstract:

The sparse array is flexible and can reduce the coupling between array elements while increasing the array aperture. However, the traditional direction of arrival (DOA) estimation based on sparse array will lead to angle fuzzy aliasing, resulting in poor estimation accuracy and insufficient robustness. In view of the above problems, a robust matrix completion algorithm for sparse array DOA estimation based on weighted truncated singular value projection (WT-SVP) is proposed. In the filling iteration process, weights are allocated according to the size of singular values to highlight the array information contained by large singular values and reduce unnecessary noise information in small singular values, so as to optimize the traditional singular value projection algorithm. The algorithm can realize the hole information recovery of sparse array and make full use of discontinuous elements. Meanwhile, the WT-SVP completion algorithm realizes the high precision, high resolution and high robustness of sparse array DOA estimation at low signal-to-noise ratio and low fast beat.

Key words: sparse array, matrix completion, singular value projection, direction of arrival (DOA) estimation

CLC Number:

TN953

Yunmeng ZHANG, Mei DONG, Boxiao CHEN. Robust matrix completion DOA estimation algorithm for sparse array[J]. Systems Engineering and Electronics, 2024, 46(5): 1477-1483.

Figures/Tables 9

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References 25

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Robust matrix completion DOA estimation algorithm for sparse array

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