An Improved Maneuvering Targets Tracking Algorithm

Research and development of the target tracking technology has been always widely given attention by people due to its significant position and wide application prospect in military and civil area. Many researchers at home and abroad has done deep research on it and got rich results in recent years. In the target tracking system, the interacting multiple model algorithm has got more attention because of using multiple motion models to match different target motion models and existing interacting between all models, it can not only improve tracking precision, but also has higher effect-cost ratio in the target tracking system. First, the research and development of the models and tracking algorithms is briefly reviewed, and their features and performance are presented. Considerable research is undertaken on the basic IMM estimator. The theoretical ratiocination, mathematical expression, selection of the models and parameters and its applicability are discussed. The simulation results show that, compared with single model, multiple model algorithm has wider tracking bandwidth, and can be generally applicable to maneuvering and non-maneuvering targets.Then, for high speed and high maneuvering conditions, the current statistical model and constant turning model are introduced into IMM algorithm to improve the model sets. The IMM algorithms using current statistical model or turning model are compared with basic IMM estimator by using Monte Carlo simulation. The influence of maneuvering frequency, maximum acceleration and turning rate to tracking accuracy is analyzed. The simulation results show that The IMM algorithms using current model is more effective for most conditions, so it is mostly studied here.Finally, based on IMM algorithm using current model, some improvement is done aimed at its disadvantages. First, by using weighted square residual detection to detect the target maneuver, a self-adaptive function for maneuvering frequency is proposed to form a self-adaptive algorithm. Second, the Variable Structure Multiple model(VSMM) algorithm is studied, and a Mode Group Switching(MGS) method is introduced to reduce the number of models. Third, introduce the fuzzy algorithm. The acceleration estimation is input into a fuzzy module to get maximum acceleration, based on weighted square residual detection MGS structure. Finally, the improved AVSIMM algorithm is done.The simulation results on several investigated flight paths show that the proposed algorithm can more effectively track high speed and high maneuvering targets and it is useful for engineering application.