Research On Map Matching Algorithm For Train Positioning Based On Beidou Satellite

Under the rapid development of China's railways,the links between railways and people's travel have become closer,and the safety of trains has been highly valued by everyone.Good train positioning technology is the key to ensure the safe operation of trains.The satellite positioning based on train positioning technology has always been a hot topic at home and abroad,and the Beidou satellite navigation system(BDS)is a global satellite r avigation system independently developed and operated by China.Therefore,research on train positioning technology based on BDS is very urgent for national security and social economy.In order to improve the accuracy and stability of train positioning,this paper will combine the BDS train positioning technology with the map matching algorithm to achieve the purpose of reducing train positioning error.In this paper,the train positioning map matching algorithm based on BDS is deeply studied.Firstly,the theory and technology of BDS and map matching algorithm are introduced.Based on this,a point-to-point train map matching algorithm based on BDS is proposed and verified.A map matching algorithm based on probability estimation to improve the point-to-point map matching algorithm.Finally,the paper verifies the validity and reliability of the algorithm by simulating the model.The specific research methods and innovations are as follows:1.Aiming at the problem that the accuracy of train positioning module is susceptible to interference,a point-to-point map matching algorithm based on BDS is proposed.The meshing is performed by setting the distance between adjacent marked points to realize the index of the positioning point and the marking point,and the range of the marking point corresponding to the positioning point is reduced,and the matching time is shortened;the positioning point is designed by the matching function based on the weight to matching the marked points in the grid,the point with the largest matching function is used as the best matching of the positioning points,and it is verified that the algorithm improves the real-time and accuracy of the train positioning.2.Aiming at the accuracy of map matching is limited by the accuracy of original positioning data,a point-to-point map matching algorithm based on probability estimation is proposed.By establishing a short-time error model,the least squares(LSA)method is used to extract the colored noise of the positioning information,and the accuracy of the original positioning information is improved.The map matching algorithm based on the Gauss white noise position probability estimation is used to improve the point-to-point.The map matching algorithm is verified by simulation analysis.The algorithm can improve the accuracy of the original positioning data,and verify that the algorithm can improve the accuracy of train location map matching.