低快拍下基于稀疏重构的大电磁矢量传感器阵列多维参数联合估计

doi:10.12305/j.issn.1001-506X.2021.04.02

Abstract

Abstract:

The radiation efficiency of the large-sized electromagnetic vector sensor (EMVS) is higher than that of small-sized EMVS. The study of its parameter estimation algorithm is helpful to promote the practical application of EMVS. The problem of parameter estimation in low snapshots is studied for large-sized EMVS array. A joint estimation algorithm of direction of arrival (DOA) and polarization parameters based on sparse reconstruction is proposed. Firstly, a low-dimensional block sparse representation with only DOA information is constructed. Then, the block orthogonal matching pursuit algorithm is used to recover the block sparse signal. Finally, the DOA and polarization parameters are estimated by the recovered signal. Simulation shows the effectiveness of the algorithm in limited snapshots, and the computation and accuracy of the proposed algorithm are better than that of the parameter estimation algorithm of the existing small-sized EMVS based on the sparse reconstruction.

Key words: long electric-dipole, low snapshot, sparse reconstruction, parameter estimation

CLC Number:

TN958

Binbin LI, Hui CHEN, Weijian LIU, Zhaojian ZHANG, Bilei ZHOU. Joint multi-dimensional parameters estimation for large-sized electromagnetic vector sensor array based on sparse reconstruction in limited snapshots[J]. Systems Engineering and Electronics, 2021, 43(4): 868-874.

Figures/Tables 5

References 27

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Joint multi-dimensional parameters estimation for large-sized electromagnetic vector sensor array based on sparse reconstruction in limited snapshots

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