Multiple maneuvering targets tracking in cluttered environment

State estimation and data association are the key problems in multiple maneuvering target tracking. Aimed at solving the problems of multiple maneuvering target tracking in cluttered environment, the author proposed a new algorithm (FAPDA) which combined an adaptive filtering algorithm with a fast probabilistic data association. It can achieve the better performance than joint probabilistic data association (JPDA) with slightly increased computational cost of probabilistic data association (PDA), and quickly detect the motion of the targets. Computational simulation shows the efficiency and speed ability of the new algorithm.