提取相位差变化率的一种新方法

传统的卡尔曼滤波算法提取相位差变化率时,要求相位差数据呈线性变化或近似线性变化,而这一条件往往不容易得到满足。针对以往利用相位差变化率进行单站无源定位的定位精度不高的问题,提出一种差分—卡尔曼滤波方法,综合了差分处理方法和卡尔曼滤波处理方法的全部优点,解决了卡尔曼滤波提取方法限制条件强的问题以及差分处理方法提取精度低的问题。通过仿真试验表明,差分—卡尔曼滤波方法滤波精度比差分方法高很多,比卡尔曼滤波方法适用范围更广,应用性更强。

A New Method for Estimation of Phase Difference Change Rate

With conventional Kalman filtering,it is required that the data of phase difference change linearly or nearly linearly. But in practice, this condition can not be fulfilled. To improve the localization algorithm precision for single site passive location, this pa- per presents an idea of differential-Kalman filtering, which includes the advantages of differential filtering and Kalman filtering and solves the problems of high constriction condition of Kalman filtering and low precision of differential methods. The simulation results show that the differential-Kalman filtering has much higher filtering accuracy than differential filtering,and has wider application than Kalman filtering.