摘要
针对纯方位被动目标跟踪中扩展卡尔曼滤波器容易发散,从而导致滤波精度差而且收敛速度慢的问题,文中将水下纯方位被动目标运动分析中的扩展卡尔曼滤波算法改进为衰减记忆卡尔曼滤波算法.通过对当前测量数据的利用,减小了历史数据对滤波的影响程度.对比仿真分析表明,滤波效果有所改善,提高了精度和收敛速度.
Concerning the problem of low accuracy and speed of filter in bearings-only target tracking, the algorithm of underwater bearings-only passive target motion analysis is improved from EKF to MAEKF. With the use of new data, the influence of old data to the filter has been lowered. The simulation results demonstrate that the MAEKF has better performance than the EKF in accuracy.
出处
《武汉理工大学学报（交通科学与工程版）》
2006年第5期817-819,共3页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国防预研项目资助(批准号:413040201)
