一种基于多普勒频移的GPS自适应滤波算法研究

针对接收机的动态模型对GPS定位精度的影响,提出了一种基于多普勒频移观测的高动态GPS自适应滤波算法。该算法利用GPS伪距测量值以及利用信号载波的多普勒频移所获得的伪距率测量值,在GPS动态滤波中同时观测伪距和伪距率。借助于移动目标的运动矢量模型以及GPS定位误差模型建立了滤波方程。重点讨论了运用该模型进行Kalman滤波的实现过程。仿真实验表明,该模型与传统的方差自适应模型相比,位置精度提高了32%、速度精度提高了25%,应用本文算法能够提高定位精度和改善接收机的动态性能,拓宽高精度、高动态导航的应用范围。

Research on an adapted filtering algorithm based on Doppler shift

Aiming at the effect of the dynamic model of receiver on GPS positioning accuracy,a GPS adapted filtering algorithm based on Doppler shift observation is proposed.With measurement acquired by GPS pseudo-distance and Doppler shift of signal carrier wave surveying,both pseudo-distance and pseudo-distance rate are observed in the course of GPS dynamic filtering.By means of kinetic vector model of mobile object and GPS location error model,the filtering equation are presented.Kalman filtering process using this model is primarily discussed.The simulation results indicate that location accuracy improves 26% and velocity accuracy improves 36.8% by using this model.Compared with the adapted filtering algorithm based on variance,this filtering algorithm can improve positioning accuracy and the dynamic capability of receiver,and extend application yield of high accuracy and kinematic navigation.