Infrared dim target detection and tracking based on particle filter

Since the distance attenuation and the strong noise, Infrared Radiation (IR) dim target detection and tracking is challenging in recent years. Under this circumstance, conventional particle filter track-before-detect (PF-TBD) algorithm cannot detect and track effectively. In this paper, a feasible two-layer particle filter based algorithm is proposed for this problem. The proposed algorithm can overcome the shortcomings of conventional particle filter (PF) algorithm. By introducing local particle swarm reset method and particle swarm optimization (PSO) algorithm, it is suitable for low-observable multi-target detection and tracking, and has a good performance of infrared dim target detection and tracking in simulations.