基于耦合张量分解的稀疏阵列二维DOA估计算法

doi:10.12305/j.issn.1001-506X.2023.04.03

Abstract

Abstract:

The traditional sparse array direction of arrival (DOA) estimation based on tensor decomposition usually divides the covariance matrix directly to construct the full rank tensor, but this method does not consider the structural information between data, which makes the information underutilized. To solve this problem, an improved tensor decomposition algorithm based on the coupling relationship between data is proposed. According to the structural characteristics of information, two third-order tensors which can use the coupling characteristics in elevation and azimuth dimensions are constructed. Two sets of angle values are estimated by tensor decomposition. The angle value estimated by using the coupling characteristics is used as the DOA value, and the accompanying estimated value is used as the angle matching. Simulation results show that the proposed algorithm can further improve the utilization of coupling information between data and effectively improve the accuracy of two-dimensional DOA estimation.

Key words: coupling tensor, sparse array, direction of arrival (DOA) estimation

CLC Number:

TN953

Mingjian REN, Guoping HU, Hao ZHOU, Zhiyuan YOU, Lingpei ZHANG. DOA estimation algorithm with two-dimensional sparse array based on coupling tensor decomposition[J]. Systems Engineering and Electronics, 2023, 45(4): 958-964.

Figures/Tables 7

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References 23

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DOA estimation algorithm with two-dimensional sparse array based on coupling tensor decomposition

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