Information Fusion of Target Motion Elements in UUV Swarm for Tracking Tasks

Due to the harsh underwater environment exist issues such as weak perception capability, difficulty in information fusion, and time delays and packet loss in underwater communication when UUV swarms perform tracking tasks. To achieve stable tracking of targets by UUV swarm, this paper focus on the fusion of motion element information for UUV swarm target tracking tasks. A target estimation method based on multiple model interactive filtering is adopted at the edge nodes to achieve flexible switching and accurate estimation of different motion models. A sub-central node target state fusion algorithm based on time-delay Kalman filtering and distributed optimal weight filtering is further designed to estimate the state of the global target. Simulation results show that the proposed algorithm can achieve perception and tracking of motion elements for multi-motion pattern targets under conditions of time delays and packet loss communication.