摘要
采用卡尔曼滤波器对目标进行跟踪时,目标初始状态估计是影响初始阶段跟踪精度的一个重要原因。该文基于无先验数据和有先验数据二种情况,提出了由前二点测量值及弹道导弹自由段的特性建立初始估计的方法和依据雷达系统之间数据转换建立初始估计的方法。仿真结果表明,使用前一种方法建立初始估计,能使滤波器迅速收敛,提高初始阶段的跟踪精度;使用后一种方法建立初始估计,能较好地实现对先验数据的利用,提高初始阶段的跟踪精度。
When using Kalman Filter to track a target, estimation of the initial state of the target is an important factor influencing tracking precision in the initial phase. In this paper, based on both without and with existing data, two methods for establishing the initial estimation are given: to establish the initial estimation through the first two measurements and the characteristic of the Ballistic Missile in Its Free - flying Phase; to establish the initial estimation through data transition between radars. Simulation results show that the former can increase the speed of convergence, improve tracking precision in the initial phase; the latter can make good use of the existing data, improve tracking precision in the initial phase.
出处
《计算机仿真》
CSCD
2006年第6期77-81,146,共6页
Computer Simulation
关键词
卡尔曼滤波算法
初始估计
跟踪精度
Kalman filter
Estimation of the initial state
Tracking precision