摘要
基于全球导航卫星系统(Global Narigation Satellite System,GNSS)的列车定位系统降低了铁路建设与运营的成本,而正确识别列车所在道岔区段是列车卫星定位的前提.为提高列车轨道占用判别过程的准确性及实时性,提出一种基于粒子滤波(Particle Filter,PF)的列车轨道占用判别方法.以PF原理为基础,根据列车当前位置,设置可调节误差置信区域对相邻道岔节点进行检索,有效避免漏检索、重复检索的问题.其次,将轨道占用判别过程建模为列车运行位置与线路地图候选区段的实时匹配过程,在与之拓扑连接的候选道岔区段上随机生成粒子进行列车的实时追踪;将各时刻粒子运动状态与列车定位点之间的距离误差及航向角误差作为加权函数,通过计算与道岔节点邻接轨道区段的累计粒子权值,得出最大概率占用区段,实现对列车所在道岔区段的正确判别.最后,结合实测数据与现有轨道占用判别方法进行对比.实验结果表明:基于粒子滤波的列车轨道占用判别方法可以有效识别当前轨道,其平均识别距离比直接投影方式稳定识别占用轨道的距离减少了约6.5 m,比加权识别方法减少了约3.8 m,具有一定实时性.
The GNSS-based train positioning system reduces the cost of railway construction and operation.And the correct detection of the turnout section where the train is located is a prerequisite for train satellite positioning.To improve the accuracy and real-time performance of the train track occupancy detection process,a Particle Filter(PF)-based train track occupancy detection method is proposed.First,based on the PF principle,an adjustable error confidence zone is set to retrieve the adjacent turnout nodes according to the current position of the train,effectively avoiding the problems of missed retrieval and repeated retrieval.Second,the track occupancy detection process is modeled as a real-time matching process between the train running position and the candidate sections of the route map.And particles are randomly generated on the candidate turnout section connected with the train to track the train in real time.The distance error and heading angle error between the particle motion state and the train positioning point at each moment are used as weighting functions.By calculating the cumulative particle weights of the track sections adjacent to the turnout nodes,the maximum probabil‐ity of occupying the section is derived to achieve the correct detection of the turnout sections where the train is located.Finally,the measured data is compared with the existing track occupancy detection method.The experimental results show that the PF-based train track occupation detection method can effectively identify the current track.And its average detection distance is stable and is reduced by about 6.5 m compared with the direct projection method and reduced by 3.8 m compared with the weighted recognition method,with great real-time performance.
作者
袁祎
陈光武
李朋朋
刘洋
YUAN Yi;CHEN Guangwu;LI Pengpeng;LIU Yang(a.Key Laboratory of Opt-electonic Technology and Intelligent Control Ministry of Education,Lanzhou Jiaotong University,Lanzhou 730070,China;School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Gansu Provincial Key Laboratory of Traffic Information Engineering and Control,Lanzhou Jiaotong University,Lanzhou 730070,China)
出处
《北京交通大学学报》
CAS
CSCD
北大核心
2022年第5期107-113,共7页
JOURNAL OF BEIJING JIAOTONG UNIVERSITY
基金
国家自然科学基金(61863024)
甘肃省科技引导计划(2020-61)。
关键词
GNSS
列车定位
轨道占用判别
粒子滤波
GNSS
train positioning
track occupancy detection
particle filter:
