Autonomous Railway Track Detection Using Innovative Satellite Signal Map Matching Technique

Jeffrey Yu, Kirusshanth Thavarajah, Loïc Boyer, Philippe Laviron, Pierre Louvé, and Sébastien Vichard

Peer Reviewed

Abstract:	The proposed paper introduces the Satellite Signal Map matching technique and the derived integrity methods with a focus on the railway domain. The innovative technique results in the application of a correlation computation between the received GNSS signal and a predicted PRN code for a chosen satellite, chosen epochs and a known georeferenced point from the map. In fault free conditions, matching is expected when the user’s antenna is located at the georeferenced point. The level of the correlation and the observed delays are used to evaluate the matching. Several consolidation methods can then be used, taking advantage of the whole set of available satellites. This approach is well suited to the track detection case of railway navigation when no previous knowledge of the position is given (at train cold start), as the algorithm is detecting a known position, while most of the current GNSS algorithms are estimating a position. Several methods derived from SSM main principles are introduced in this paper.
Published in:	Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1706 - 1720
Cite this article:	Yu, Jeffrey, Thavarajah, Kirusshanth, Boyer, Loïc, Laviron, Philippe, Louvé, Pierre, Vichard, Sébastien, "Autonomous Railway Track Detection Using Innovative Satellite Signal Map Matching Technique," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1706-1720. https://doi.org/10.33012/2024.19918
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