同济大学学报（自然科学版）2024，Vol.52Issue(6)：935-942,8.DOI:10.11908/j.issn.0253-374x.22394
基于抗差自适应滤波的高速列车融合测速算法
Fusion Speed Measurement Algorithm of High-speed Train Based on Robust Adaptive Filter
摘要
Abstract
A fusion speed measurement algorithm of high-speed trains based on robust adaptive filter was proposed to solve the problem that the fusion accuracy decreased due to the observation gross errors and the dynamic model errors in the fusion speed measurement using Kalman filter.Firstly,the anomaly detection function and error discrimination statistics were constructed on the basis of Kalman filter,which were used to detect and distinguish the observation gross errors and dynamic model errors caused by abnormal observations of sensors.Then,for observation gross errors and dynamic model errors,a three-segment function and an exponential function were used to construct robust factor and adaptive factor,respectively.The weights of observation information and model information in state estimation were reasonably adjusted by the two factors,so as to reduce the impact of observation gross errors and dynamic model errors on the fusion results.Finally,the performance of robust adaptive filter was verified by simulation with two operation scenes and comparison between algorithms.The simulation results show that compared with the fusion speed measurement algorithm based on Kalman filter,the proposed algorithm has higher accuracy and stability in both the observation gross errors scene and the dynamic model errors scene.关键词
铁路运输/列车测速/抗差自适应滤波/高速列车/信息融合Key words
railway transportation/train speed measurement/robust adaptive filter/high-speed train/information fusion分类
交通工程引用本文复制引用
王小敏,贾钰林,张亚东,魏维伟,何静..基于抗差自适应滤波的高速列车融合测速算法[J].同济大学学报（自然科学版）,2024,52(6):935-942,8.基金项目
中国国家铁路集团有限公司科技研究开发计划(P2021G053,N2021T008,N2021G045) （P2021G053,N2021T008,N2021G045）
上海航天科技创新基金(SAST2020-126) （SAST2020-126）
