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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Vydané v:Journal of physics. Conference series Ročník 2458; číslo 1; s. 12015 - 12021
Hlavní autori: Su, Peilin, Huang, Di, Zhu, Jieqi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bristol IOP Publishing 01.03.2023
Predmet:
Greedy algorithms
Physics
ISSN:1742-6588, 1742-6596
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Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2458/1/012015