Multisource Target Classification Based on Underwater Channel Cepstral Features

Passive target detection through shipping-radiated noise is a key technology in current underwater operations and is of great research value in civil and military fields. In this study, the stable spectral line component of shipping-radiated noise is used as the research object, and the classification of multisource targets is studied from the perspective of underwater channels. We utilize the channel impulse response function as the classification basis of different targets. First, the underwater channel is estimated by the cepstrum. Then, the channel cepstral features carried by different spectral line components are extracted in turn. Finally, the spectral line components belonging to the same target are clustered by the cepstral feature distance to realize the classification of different targets. The simulation and experimental results verify the effectiveness of the proposed method in this research.