A CKF based GNSS/INS train integrated positioning method

Train positioning with high precision and integrity is crucial to train control system. For conventional positioning methods in multi-sensor integration frame could not meet the performance requirements, a GNSS/INS integrated positioning system architecture is built, in which the cubature Kalman filter is analyzed and employed to solve the problem of nonlinearity and computation efficiency, and the integrity design is realized by the principal component analysis based fault detection and diagnosis. Validation with practical measurement and results of simulation demonstrate that the CKF approach earns a high accuracy and efficiency ability than traditional UKF and PF solutions, and the integrity performance of the train positioning system could be improved by the PCA based FDD strategies.