A fuzzy adaptive tracking algorithm based on current statistical probabilistic data association

In this paper, a new fuzzy adaptive maneuvering target tracking algorithm based on current statistic model is proposed. How to track a maneuvering target is a key problem of target tracking in clutter. Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets. So it may be difficult to meet all maneuvering conditions. The Fuzzy inference combined with Current statistical model is proposed to cope with this problem. Given the error and change of error in the last prediction, fuzzy system on-line determines the magnitude of maximum acceleration to adapt to different target maneuvers. Furthermore, the difficulties of the maneuvering target tracking lies in the uncertainty of state model, and the clutter make it more complex. The algorithm combines current statistical algorithm with probabilistic data association algorithm. At last, the results show this algorithm can estimate a maneuvering target in clutter efficiently.