Underwater acoustic multi-target recognition algorithm based on hierarchical information fusion structure

Liang Yu, Yongmei Cheng, Lin Song, Zhunga Liu, Ke-zhe Chen

Abstract: In the complex hydroacoustic countermeasure environment, submarine often release a variety of decoys to disrupt the attack. Because the current electronic technology is able to produce high quality decoys, it is very difficult to correctly recognize the real submarine by the spectral analysis method. During the tracking process, a hierarchical multi-source information fusion structure is designed based on evidence theory for identification of the submarine. In the beginning, the observed acoustic data are divided into two types: target acoustic feature data and motion feature data. The sources of information obtained from different features in the same type are fused respectively at the first fusion level. The two pieces of fusion results are weighted combined at the second level. The sequential feature information (i.e. the multi-temporal fusion results at the second level) in the time domain will be selected according to the current context to enter the fusion process at the third level for the final identification of targets. Simulation results show that the proposed method can effectively identify acoustic targets.