Research on speed measurement accuracy of high-speed train based on longitudinal and transverse multi-speed fusion
Hou Tao
Zhao Tingyang
Abstract：In view of the common issues of significant speed measurement errors and low operational efficiency in high-speed train systems,this study introduces a speed measurement method based on longitudinal and transverse multi-speed fusion.Firstly,the process begins by collecting speed data from four speed sensors through stacked sampling.The Federal Kalman filtering algorithm is applied to filter each of the four speed values longitudinally.The decay memory method is incorporated to ad-dress filtering dispersion issues,obtaining the 4 longitudinal fused speed values.Secondly,a confi-dence distance reliability of the four longitudinal fusion speed values is used to determine the number of valid fusion speed values,eliminating the impact of sensor failure.Thirdly,an improved Bayesian data fusion algorithm is employed to transversely fuse the valid longitudinal fused speed values.Finally,the algorithms are simulated,and the analysis and comparison of the simulation results are completed.The results show that the average error in the longitudinal fusion speed,when using the Federal Kalman filtering algorithm based on the decay memory method,is 0.669 6 km/h.On the other hand,the average error in the fusion speed,utilizing the longitudinal and transverse multi-speed fusion method,is 0.392 8 km/h,marking a substantial enhancement in average speed measurement accuracy.
Keywords：speed measurement accuracylongitudinal and transverse multi-speed fusionFederal Kalman filterattenuation memory methodBayesian data fusion
Publication Date：2023-10-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 48-55 )