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Title: A novel GNSS-based positioning system to support railway operations
Author: Damy, Sophie
ISNI:       0000 0004 6421 0963
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
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While railway relies on the knowledge of train position to manage operations, systems currently used to locate trains have a limited accuracy, which limits the network capacity. A positioning system combining Global Navigation Satellite Systems (GNSS) with additional sensors has the capability to provide high accuracy positioning information to support railway operations. However, to reach such accuracy, the different sources of error affecting GNSS measurements need to be mitigated. Among these error sources, multipath signals are a prime concern as they are particularly challenging to mitigate due to their high variability along the train path. The aim of this thesis is to mitigate the effect of multipath on GNSS code based single point positioning in the railway environment. To achieve this aim, the code multipath error in the railway environment is characterised. Measurement weighting techniques traditionally used to mitigate the effect of multipath on the positioning solution are investigated and a novel weighting method based on the train heading and the satellite position is developed and tested. The results show variable levels of performance, with no single method outperforming the rest along the entire track dataset analysed. In summary, the elevation and the new heading based methods are shown to complement each other, with the latter performing better (34% of the time) where there are trackside obstacles.
Supervisor: Ochieng, Washington ; Majumdar, Arnab Sponsor: Lloyd's Register Educational Trust
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral