Underwater acoustic target optimum seeking using evidence theory

Decoys and real submarines exist simultaneously and are hard to be recognized with frequency analysis in underwater acoustic countermeasure environment. During the tracking process, a novel identification algorithm using the acoustic feature and motion feature information for target optimum seeking method is proposed; this novel algorithm was implemented with evidence theory. Through the study of underwater acoustic target attributes, the desired attributes for optimum seeking were given and modeled. First suitable target attributes were proposed; next membership degrees of these attributes were respectively computed; then the acoustic features and motion features were respectively fused; at last, weighted fusion was done to the acoustic feature and motion feature fusion results. Discrete simulation and experimental results and their analysis show preliminarily that the proposed algorithm can identify the targets effectively.