基于贝叶斯模型的列车定位精度提升方法

A Method for Improving Train Positioning Accuracy Based on Bayesian Model

我国高铁快速发展对新型列车控制系统提出了更新更高的要求,基于北斗卫星导航的列车定位技术是控制系统研究重点。而铁路沿线环境复杂多变,沿线两侧高山、建筑物、森林等形成的遮挡环境会对北斗卫星导航信号传播造成遮挡和反射,导致卫星定位性能下降,列车定位精度受到严重影响。本文提出一种基于贝叶斯模型的卫星定位加权解算方法,通过对观测位置下所有卫星信号信噪比(Signal-Noise Ratio,SNR)进行统计,构建卫星信号强度贝叶斯模型,对参与解算的卫星分配不同权重,可有效解决现有列车定位技术在卫星信号部分遮挡环境下定位精度下降的问题。

The rapid development of high-speed railways in China has put forward new requirements for new train control systems,and the research focus of the system is on train positioning technology based on Beidou satellite navigation.The environment along the railway is complex and variable,and the obstructed environment formed by high mountains,buildings,forests,etc.on both sides of the line can cause obstruction and reflection of the propagation of Beidou satellite navigation signals,leading to a decline in satellite positioning performance and a serious impact on the accuracy of train positioning.This article proposes a satellite positioning weighted solution method based on a Bayesian model.By statistical analysis of the Signal Noise Ratio(SNR)of all satellite signals at observation positions,a Bayesian model of satellite signal strength is constructed.Different weights are assigned to the participating satellites in the solution,which can effectively solve the problem of reduced positioning accuracy in existing train positioning technology under partial occlusion of satellite signals.