Abstract

The train positioning plays a key role in the train control system. The current train positioning is determined by the track circuit or balise, which cost a lot to build and maintain. GPS (Global Positioning System), one kind of GNSS (Global Navigation Satellite System) positioning technology, provides a cheap and real-time option. However, the inherent defect of GPS positioning is the socalled incomplete condition of GPS when less than four satellites are effective. This paper presents a new train GPS positioning algorithm based on the digital track map and optimization method for the incomplete condition of GPS. First, the track piece where the train is located is identified at the moment when the GPS satellite signals become incomplete. Then, a straight-line equation constrained by the pseudo-range equation is deduced. Finally, the estimated train position is obtained by minimizing the sum of the squared errors, which is solved by the gradient descent method and compared with the actual location in the digital track map. After the experiments were carried out in Sanjia dian Station, Beijing Railway Station, to get the field GPS positioning data, the performance of the proposed algorithm was evaluated and analyzed. The results demonstrated that the accuracy and stability of train positioning employing the proposed method were improved in GPS satellite incomplete condition (SIC).

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