A method for target detection in complex acoustic environments using unmanned underwater vehicle motion

In acoustic target detection using an unmanned underwater vehicle (UUV), platform self-noise and ambient noise emerge as dominant constraints on detection performance. In complex acoustic environments, flow noise, propeller noise, and ambient noise exhibit distinct spectral and spatial characteristics. Their partial overlap with target signals in frequency and spatial domains leads to degradation in noise suppression performance. To address this issue, this paper investigates the characteristics of signals and noise during UUV motion. While platform self-noise and ambient noise remain relatively stable, the incidence angle of signal varies with the platform's heading angle. This paper exploits this phenomenon to achieve signal-noise separation and develop a method for suppressing complex noise. The goal is to enhance the detection performance of weak targets. Experimental results demonstrate that the proposed method requires little prior information, effectively suppresses complex noise, and does not compromise the integrity of the target signal.