基于“当前”统计模型的模糊自适应跟踪算法

我存的一篇论文，拿来与大家共享-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,in tracking problem

many measurement equations are non-linear.Unscented Kalman filter is applied instead of extended Kalman filter.The

Monte Carlo simulation results show that this method outperforms the conventional tracking algorithm based on current

statistical model in both tracking accuracy and convergence rate.