关键词: 机动目标跟踪, 非线性预测, 自适应扩展卡尔曼滤波算法, Monte Carlo仿真

Abstract: In the tracking and orientation of maneuvering targets，a new nonlinear Adaptive Extended Kalman Filter（AEKF） algorithm based on current statistical model is proposed，due to nonlinear character of the system connect with the excellence of the extended Kalman filtering and the adaptive theory.It expresses variation of acceleration with the information of position and angle to carry out self-adaption，and eliminates random error and noise variance to elevate the accuracy of tracking.Analytic results of Monte Carlo simulation proves the AEKF algorithm is right and feasible，and the accuracy and the stability are both improved.It has better performance than the traditional EKF，Modified Variance EKF（MVEKF） algorithms.The method affordes a new application to the tracking and orientation of maneuvering targets.

Key words: tracking of maneuvering target, nonlinear prediction, the Adaptive Extended Kalman Filter（AEKF） algorithm, Monte Carlo simulation