基于线路数据信息的列车定位方法研究

Aimed at the problem that the train loses satellite signal and can not be located, a dynamic time warping (DTW) based train smoothness information matching algorithm is proposed. With the help of specific sensor, the online regularity information of the train is collected. Afterward, the collected data is processed and matched by applying DTW-KF (Kalman filter). Using the data measured by the onboard speed sensor as template variables, the online regularity measurement data is applied to do the matching. According to the optimal matching path, distortion, and matching results of DTW, the train can be positioned offline when the train cannot be located due to the loss of the satellite signals. The template data is divided into blocks (even division and quartile) to match in real-time, and the error correction of the INS (inertial navigation system) based on the matching result of the DTW algorithm can locate the train when the satellite signal loses online location information.