Abstract: The precise train positioning under complicated railway environment has been a key technical challenge for train navigation currently. In the conventional solutions, in case of satellite signals being weak or indiscernible, the task of positioning has to be undertaken by SINS alone. This will cause some serious error-accumulation problems, especially when low-cost inertial devices are used. In order to solve this problem, we propose a novel integrated train navigation algorithm, which includes two working modes. The SINS/GNSS mode is designed for the situation that satellite signals are valid, whereas the SINS/wheel-speed mode is for the weak signal environments. Both simulation results and measured data show that the proposed algorithm can achieve a much higher accuracy, i.e., the maximum horizontal error is less than 5m in case that the satellite signals are frequently invalid for a short time (<90 s).

Key words: train positioning, strapdown inertial navigation, integrated navigation, Kalman filter