A maneuvering target tracking algorithm based on amplitude characteristics in sea clutter

Aiming at the problem of maneuvering target tracking in the background of sea clutter, this paper adopts a method based on the combination of probabilistic strongest neighbor filter algorithm with m-validated measurements (PSNF-m) and adaptive Interactive Multi-Model (AIMM). First, the PSNF-m algorithm uses echo amplitude characteristics to carry out echo correlation, and then uses adaptive interactive multi-model to filter the data after correlation, so as to realize the tracking of maneuvering targets. In this paper, the sea clutter background is simulated by K distribution. The corresponding measurement likelihood is given, and the corresponding simulation is carried out. Simulation results show that the algorithm proposed in this paper can effectively track maneuvering targets under sea clutter, and has better performance than the traditional amplitude assisted Interactive Multi-Model probabilistic data association with target amplitude feature (IMM-PDA-AI) and Interactive Multi-Model strongest neighbor (IMM-SNF).