摘要
把方位作为被动传感器的观测信息属于不完全观测.文中的方案是先用最小二乘法估计出目标距离,再用卡尔曼滤波进行跟踪.单一的被动传感器定位需要机动,而多个被动传感器联合工作,可以在观测站静止的情况下完成定位.通常的最小二乘是寻求到各传感器的方向线距离平方和最小的点,而文中选择另一种推导方法,由于该方法也用到最小二乘理论,亦称最小二乘法.文中将该方法与卡尔曼滤波结合进行目标跟踪仿真,结果表明该方法是有效的.
The observed information of a passive sensor is azimuth, and it belongs to incomplete observation. In this paper, the range information is estimated by the least square method, then linear Kalman filter is applied for track- ing target, Maneuvering is necessary for the location of a single sensor, however, the task of ~ocating may be ~n]- filled by the combined operation of many sensors in the case of stationary observatories; The traditional least square method is to seek for the point which has the least distance square sttm away from the direction line of each sensor. In this paper, another derivation method is selected, Because the least square theory is also used in this method, it is also called the least square method, which is combined with the Kalman filter for target tracking and simulation. The results show that the method is efficacious.
出处
《应用科技》
CAS
2013年第6期20-23,共4页
Applied Science and Technology
关键词
不完全观测
机动
静止
被动多传感器
最小二乘
卡尔曼滤波
incomplete observation
maneuvering
stationary ~ passive multiple sensors i least sqnare
Kalman filter.