Integrated Train Positioning Information Fusion Algorithm Based on SR-UIF
LI Weidong
WANG Yi
WANG Yunming
WANG Xinping
Abstract：Aiming at the problem that the current BDS/INS positioning system model is used in train positioning due to large noise,which leads to low positioning accuracy,a train tightly coupled combined positioning system model based on BDS/INS is de-signed,and the system state equation and measurement equation considering various factors are established.A train location infor-mation fusion algorithm based on square-root unscented information filtering(SR-UIF)is proposed.The algorithm uses unscented transformation to process the mean and covariance of the system equation,obtains the corresponding Sigma point set and its weight,and obtains sampling points with different weights.The square root estimates the mean and variance of the system state at the next moment,reducing the computational complexity and the impact of noise.The simulation analysis shows that,compared with the UKF algorithm,in the driving section where satellite signal can be received normally,the SR-UIF algorithm reduces the influence of noise on the train positioning system,reduces the position error and speed error of the train,and improves the accuracy and re-al-time performance of the train positioning.In the driving section where the satellite signal is out of lock,the SR-UIF algorithm can still solve the positioning information with high accuracy and relative stability within a certain period of time,which can provide reliable operation information for the train.
Keywords：train combination positioningBDS/INSinformation fusionsquare-root unscented information filteringinfor-mation matrix
Publication Date：2025-09-20
Online Publishing Date：2025-12-23(First online date of this platform, not the publication date of the document)
Pages：6( 2484-2488,2496 )