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A DOA Estimation Method Based on an Improved Transformer Model for Uniform Linear Arrays with Low SNR.

Authors :
Wei Wang
Lang Zhou
Kun Ye
Haixin Sun
Shaohua Hong
Source :
IET Signal Processing (Wiley-Blackwell); 2/17/2024, Vol. 2024, p1-25, 25p
Publication Year :
2024

Abstract

In this paper, the Star-Transformer model is improved to obtain more accurate direction of arrivals (DOA) estimation of underwater sonar uniform linear array (ULA) under low signal-to-noise ratio (SNR) conditions. The ideal real covariance matrix is divided into three channels: real part channel, imaginary part channel, and phase channel to obtain more input features. In training, the real covariance matrix is used under different SNRs. In testing, the covariance matrix of samples in the real environment is used as input. The on-grid form is used to estimate the DOA of multiple signal sources, which is modelled as a multilabel classification problem. The results show that the model can be effective and can still have a good DOA estimation performance under the conditions of trained and untrained SNRs, different snapshots, signal power mismatch, different separation angles, signal correlation, and so on. It shows that the model has excellent robustness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17519675
Volume :
2024
Database :
Complementary Index
Journal :
IET Signal Processing (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
177978454
Full Text :
https://doi.org/10.1049/2024/6666395