A Multi-Sensor Positioning Method-Based Train Localization System for Low Density Line

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Abstract
The BeiDou Navigation Satellite System (BDS) has been widely applied in many areas, including communications, transportation, emergency rescue, public security, surveying, precise positioning, and many other industrial applications. The integration of BDS and an Inertial Navigation System (INS) has the ability to achieve a more consistent and accurate positioning solution. However, during long BDS outages, the performance of such an integrated system degrades because of the characteristics of the Inertial Measurement Unit (IMU) - the sensor errors accumulate rapidly with time when operated in a standalone mode. In this paper, a BDS/INS/odometer/map-matching (MM) positioning methodology for train navigation applications is proposed, to solve the problem of positioning during BDS outages when trains pass through signal obstructed areas such as under bridges, inside tunnels and through deep valleys. The seamless transition of the train operation in various scenarios can be therefore maintained. When the train operates in an open-sky environment the BDS signals are available to provide accurate positioning, and the integrated BDS/INS/odometer/MM system is used to correct the INS errors using BDS measurements and to calculate the velocity using the odometer in the navigation frame so as to improve the system reliability and accuracy. In addition, the integrated system also delivers accurate positioning measurements at a high update rate. When the BDS signals are blocked the integrated system switches to the INS/odometer/MM mode, and the integrated system corrects the INS errors by using odometer measurements. In order to evaluate the proposed system a real experiment was conducted on the Qinghai-Tibet railway in western China. The experimental results indicate that the proposed system can provide accurate and continuous positioning results in both open-sky and BDS signal-obstructed environments.
Funding Information
  • State Key Project of Chinese Ministry of Science and Technology (2018YFB1201500)
  • National Natural Science Foundation of China (61703034)
  • Beijing Natural Science Foundation (4184096)

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