基于小二乘-卡尔曼滤波的wMPS系统跟踪定位算法研究

Study on Tracking Algorithm for wMPS Based on Least Square-Kalman Filter

wMPS(workspace Measuring Position System)是一种新型的基于平面交会原理的网络式测量系统,在静态测量研究的基础上,研究了动态跟踪测量的问题。为了减小运动引入的测量误差,利用运动方程提高测量精度,采用了最小二乘法对接收器的位置进行静态估算,将其结果作为伪观测值,然后利用卡尔曼滤波做进一步处理,该方法避免了观测方程中的非线性误差,实现了接收器在运动过程中的高精度跟踪定位。通过试验对最小二乘法和最小二乘-卡尔曼滤波法进行了比较,结果表明最小二乘-卡尔曼滤波法的估值精度远高于最小二乘法。

wMPS（workspace Measuring Position System）is a newly network-type three-dimensional measuring system based on plane intersection principal.The dynamic tracking problem was studied based on the static measurement research.In order to reduce the errors produced by movement,motion model and Kalman filter were used.The static-location of receiver was used as pseudo-observations,which was estimated by least square method,and the results were used by Kalman filter for further processing.This method avoids nonlinear errors in observation equation and the precision tracking was achieved.Compared with least square method and least square-Kalman filter method in experiments,the results show that the accuracy of least square-Kalman filter method is higher than least square method.