Research on Improved EKF Train Positioning System Based on Mode Switching Strategy

In complex scenarios like tunnels and forest areas, the speed measurement and positioning systems of trains often face challenges. For instance, there may be sudden changes in the system state, and satellite signal interference can lead to the failure of obtaining accurate position data. To tackle these problems, this paper puts forward an adaptive switching approach between the GNSS/SINS and SINS/OD positioning modes. This method can ensure precise positioning even when satellite signals are lost. Moreover, a new anomaly detection method is introduced in the Extended Kalman Filter (EKF) algorithm. By correcting the one-step predicted values, this method improves the positioning accuracy under abnormal conditions. The simulation results show that the proposed system can still maintain high positioning accuracy in situations where satellite signals are lost or there are sudden state anomalies.