【摘要】 列车精确自主定位是列车运行防护过程的一项核心关键技术。提出一种基于全球导航卫星系统同时考虑轨道占用状态转移的贝叶斯估计算法，将列车可能占用的区段放入备选集合，并对备选集合不断更新、评估、选择。在静态初始定位过程中，使用极大似然估计算法计算列车在区段上最可能的位置；在跟踪定位过程中，使用卡尔曼滤波算法将全球导航卫星系统和速度传感器融合实现精确定位。对列车实际行车数据分析的结果表明：在静态初始定位过程中，占用轨道识别正确率为100%;在跟踪定位过程中，占用轨道识别正确率为100%,平均误差为0.76 m。本方法满足列车运行防护的运用要求，对卫星导航定位在铁路中的应用具有借鉴意义。更多还原

【Abstract】 Accurate autonomous positioning of trains is a key technology in the process of train operation protection. A Bayesian estimation algorithm was proposed based on Global Navigation Satellite System(GNSS) considering the transfer of track occupancy state. The sections that may be occupied by the train were put into the alternative set, which was continuously updated, evaluated and selected. In the static initial positioning process, the maximum likelihood estimation algorithm was used to calculate the most likely position of the train in the section. In the process of tracking and positioning, the Kalman filter algorithm was used to fuse GNSS and velocity sensors to achieve precise positioning. The results of GNSS data analysis on the actual train operation show that the accuracy of occupied track recognition is 100% in the static initial positioning process. In the process of tracking and positioning, the recognition rate of occupied track is 100%, with the average error of 0.76 m. This method, meeting the application requirements of train operation protection, has reference significance for the application of satellite navigation and positioning in railways.更多还原