MTSA-Net: A multiscale time self-attention network for ship radiated self-noise reduction

Hailun Chu,Chao Li,Haibin Wang,Jun Wang,Yupeng Tai,Yonglin Zhang, Lei Zhou,Fan Yang, Yannick Benezeth

OCEAN ENGINEERING(2024)

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摘要
For a surface ship carrying a towed array, its in-band radiated self-noise is one of the near-field strong interference, which will seriously limit the performance of the underwater acoustic (UWA) signal detection system. Typically, the conventional ship noise cancellation methods requires time-synchronized hydrophone arrays, such as the towed linear array (TLA), to suppress its self-noise by using spatial filters. However, the spatial filter based methods fail when the direction of arrival of the desired signal is in the ship noise masking area. In cooperative scenarios, the prior knowledge of the template signal provides additional temporal information, which can be utilized to design a time-domain representations based detection system. In this paper, a multiscale time self-attention network (MTSA-Net) is proposed to mitigate the ship radiated self-noise and enhance the desired signal to improve the performance of signal detection system. Experimental results based on sea trial data indicate the effectiveness of our proposed method.
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关键词
Underwater signal detection,Ship radiated self-noise,Deep learning,Self-attention,Low signal-to-noise ratio
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