一种基于ARMA新息模型的机动目标跟踪算法

A Maneuvering Target Tracking Algorithm Based on ARMA Model

针对一般机动目标跟踪算法的复杂性和计算量大的缺点,提出了一种基于ARMA新息模型的改进稳态Kalman滤波算法。该算法选取极坐标系为跟踪坐标系,将反映径向加速度和机动角加速度的控制输入量引入到目标距离和方位的状态描述模型中,其计算量远远小于一般跟踪算法。仿真试验结果表明该算法满足机动目标跟踪的精度要求,可应用于机动目标的快速跟踪。

Due to the complexity of some algorithms and the great quantity of calculation for maneuvering target tracking,this paper presents a modified Kalman filtering algorithm based on ARMA model.This algorithm appends the acceleration of azimuth and distance as the term of state estimation in polar coordinates.The quantity of this new algorithm requires much lower computational load than the common algorithms.The simulation results show that the new algorithm can gain high calculation accuracy,which can be applied for fast maneuvering target tracking.