Maneuvering Target Tracking Algorithm And Applied Research

The subject of Maneuvering Target Tracking (MTT) has an application in national defense, the processing of radar and sonar signals and other related areas. The researchers all over the world have been engaged in the area for the recent decades, and many plentiful and substantial results have been acquired, which have been widely applied to military fields such as air reconnaissance and early warning, ballistic missile defense, battlefield surveillance, etc; and some civil fields such as air traffic control, intelligent vehicle system, traffic navigation and robot vision system, etc. With the high-tech developing quickly, various applied systems have been asking the theoretic development for more and more complex desires.The basic principles of MTT are introduced in the dissertation; then, the target maneuvering models, data association and filter techniques are given in this dissertation respectively. Based on these principles, the author deeply studied in the data association and adaptive filter techniques. Based on the commonly accepted "current" statistical model, the Improved Adaptive Filtering (IAF) algorithm simplifies variation of acceleration with the information of position to carry out the self adaptation of noise variance. To solve the problem of the computational burden in maneuvering target tracking in clutter, a new algorithm which combined Interactive Multiple Models-Probabilistic Data Association (IMMPDA) with an adaptive filter algorithm is presented. With the help of the adaptive factor and a new structure, the new algorithm achieved better performance than the traditional algorithm.At last, the application of intelligent technology in MTT was introduced. With the help of BP network, data fusion adaptive filtering algorithm was used to realize the state estimation and prediction without models interaction. The association algorithm, which was added the Hopfield network in, solved the problems of joint probabilistic data association algorithm. The problem of association probability can also be solved by fuzzy theory.