摘要
针对空中机动目标的被动定位跟踪问题,提出了一种先用静态估计理论对空中目标进行最小二乘估计,再采用基于“当前”统计模型的自适应滤波算法进行滤波处理的方法,取得了比最小二乘估计与卡尔曼滤波相结合的算法更好的效果。仿真结果表明,在跟踪非机动目标时,该算法和最小二乘估计与卡尔曼滤波结合的办法相当;在跟踪机动目标时,该算法的误差明显小于原算法。
Considering the problem of passive locating and tracking of a maneuvering target in the Sky, a method is proposed in which the least square estimation of target location is derived based on static estimation theory at first, and then the adaptive Kalman filter based on “current” statistical model is used to improve the location accuracy. Better effect is obtained than the algorithm combining least square estimation and standard Kalman filter. The simulation results show that the method has the same accuracy as the combining algorithm in tracking a non-maneuvering target, while it has fewer errors in tracking a maneuvering target.
出处
《红外与激光工程》
EI
CSCD
北大核心
2006年第6期728-731,737,共5页
Infrared and Laser Engineering
基金
航天支撑基金资助项目(2004)
航空科学基金资助项目(0F15002)
关键词
被动跟踪定位
最小二乘估计
“当前”统计模型
Passive locating and tracking
Least square estimation
“Current” statistical model
