Multi-source Information Fusion Based Train On-line Operation Data Monitoring and Analyzing

With the rapid development of high-speed trains in the world, how to quickly collect train operation data becomes a significant issue. The paper uses Global Navigation Satellite System (GNSS), Inertial Navigation System (INS), and Driver Machine Interface (DMI) information fusion to obtain the position and speed information of the train more accurately. Among these information sources, GNSS and INS can carry out the collection of train position and speed information with and without obstructions, respectively. When the train is running in the open and unobstructed, GNSS can directly obtain train operation information. When the train passes through an environment with obstructions, GNSS and INS work simultaneously to obtain train operation information. The DMI on the train has the timely speed and kilometer mark information of the train. During the measurement, as we can not access to the onboard equipment. The camera is applied to collect the DMI interface. The image is processed to obtain the train data information. In this paper, the train data collected by GNSS/INS equipment is corrected by the Kalman filtering method. The data collected by DMI is filtered by the kinematics theorem and the least square method. What is more, a centralized fusion structure is used to process the DMI, GNSS, and INS data. This result can provide more accurate train time, speed, and kilometer mark information for the train during the operation test.