Research on Robust CS-DOA Estimation Method Based on Signal Sparsity Reconstruction

The application of compressed sensing theory in DOA estimation of underwater signals has always been difficult. Aiming at the slow operation speed of the current L1-SVD algorithm and the poor robustness under various conditions such as multi-array elements, this paper proposes an improved CS-DOA est...

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Bibliographic Details
Published in:Journal of physics. Conference series Vol. 2458; no. 1; pp. 12015 - 12021
Main Authors: Su, Peilin, Huang, Di, Zhu, Jieqi
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.03.2023
Subjects:
Greedy algorithms
Physics
ISSN:1742-6588, 1742-6596
Online Access:Get full text
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Summary:The application of compressed sensing theory in DOA estimation of underwater signals has always been difficult. Aiming at the slow operation speed of the current L1-SVD algorithm and the poor robustness under various conditions such as multi-array elements, this paper proposes an improved CS-DOA estimation algorithm combined with the greedy algorithm. The algorithm sparsely reconstructs the received signal itself, which effectively improves the strict sparsity of the processed signal. The feasibility of the new algorithm is proved through theoretical analysis and simulation experiments. Compared with the L1-SVD algorithm, the measurement performance under different conditions is significantly improved. It has development prospects in academic research and engineering applications.
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2458/1/012015