A Feature-Aided Multiple Model Algorithm for Maneuvering Target Tracking

This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aided multi-model tracking method for maneuvering targets is proposed. Specifically, at each node, direction of arrival (DOA) estimation and model selection is performed, and information is fused in the central node where multi-model-based tracking is realized to closely monitor the target. Simulation results show that our proposed method is capable of rapidly responding to model switching and significantly improve the accuracy of maneuvering target tracking.