Infrared small target tracking based on target and interference behaviors model

A new infrared small target tracking method is proposed to track small target with existence of interference. First, interference occurrence decision algorithm is presented to decide whether the tracking method is interfered by multi-targets or infrared decoys. Second, target and interference behaviors are modeled using random finite sets (RFS). Then behaviors model based target and interference tracking method is formulated using maximum a posteriori probability which is propagated through Gaussian mixture probability hypothesis density filter (GMPHD filter). Experimental results show that the proposed tracking method can track small target and interference accurately and efficiently.