A Train Integrity Monitoring Method Based on Information Integration of GNSS and Odometer

Abstract

To effectively use the satellite data to monitor trains and achieve certain accuracy, this paper proposes a train integrity monitoring method that integrates the data of GNSS (Global Navigation Satellite System) and odometer. It is a data-fusion method and the data is mainly divided into three parts: satellite data, track data and the satellite-receiver data. In this paper, we use two odometers equipped with GNSS receivers as ground systems and a section of the Hong Kong Tun Ma Line is selected as the trajectory of the track for simulation. First, the carrier phase double difference method and Melbourne-Wübbena (MW) algorithm are applied to solve the integer ambiguity. Then, combing the data of track's tangent and the data received from satellite, the least squares estimation is applied to achieve position correction as well as odometer correction. Finally, the presented method is verified through a series of simulations. The experimental results show that the satellite-track data fusion algorithm can achieve certain accuracy to continuously correct the accumulated errors, which also provide a good continuous monitoring of the length of the train. The proposed method is expected to provide a low-cost, high-precision tool for train's integrity monitoring.