摘要
只测角单站无源定位跟踪系统中,目标初始状态估计精度较低时,采用扩展卡尔曼滤波算法经常出现滤波发散的情况。针对这一问题,提出了一种多模型扩展卡尔曼滤波方法,根据目标的初始状态估计设计了五个扩展卡尔曼滤波模型,对目标运动状态进行多模型估计,在滤波过程达到稳态后,再采用单模型滤波。仿真实验验证了算法的有效性。
In the bearings-only passive locating system with single station, the Extended Kalman Filtering （EKF） algorithm is used to diverging when the initial state estimation of.the target is of low precision. In this paper, a multiple-model EKF algorithm is presented to solve this problem. According to the initial state estimation, five EKF models are designed to estimate the motion state of the target. When the multiple-model EKF process comes to steady-state, the single-model filtering algorithm is applied. Simulation results indicate that the proposed algorithm is valid.
出处
《火力与指挥控制》
CSCD
北大核心
2007年第10期99-101,105,共4页
Fire Control & Command Control
基金
"十五"国防预研基金资助项目(41306030102)
关键词
无源定位
只测角
扩展卡尔曼滤波
多模型估计
passive location, bearings-only ,extended kalman filter ,multiple-model estimation
