Research on Train Wheel Diameter Correction Based on Multi-sensor Fusion and Gray-Scale Prediction
Multi-sensor fusion is an effective way to realize low-cost and high-precision positioning on train.And Kalman filter algorithm is easy to be applied in the computer,so it is one of the important research directions of information fusion.This paper studies on the odometer in multi-sensor fusion system and analysis of its positioning error source.Based on the fuzzy adaptive Kalman filter algorithm,the gray level prediction model is introduced and improved,and the two methods are combined to improve the real-time and autonomy of the wheel diameter correction work.Verification of measured data and results of simulation demonstrate that the proposed algorithm provides high precision,high system efficiency and improved independent performance and it is of some value in application.
multi-sensor train positioning gray prediction Kalman filtering
Teng Zhong Shenghua Dai
School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing,China
国际会议
深圳
英文
33-36
2018-01-21（万方平台首次上网日期，不代表论文的发表时间）