GNSS Signal in Railway Train Operation Scenario Quality Grid Generation Method

Abstract

Railway train operation requires accurate and reliable location for train dispatching and control. GNSS(Global Navigation Satellite Systems) provides continuous location for many railway application as track survey, dangerous goods monitoring, timing and also train localization for train control purposes on lines like Chicago-Detroit Line, Qinghai-Tibet railway, etc. As the train operates and travels along the railway track through railway stations, sections, shunting yards, the GNSS signal propagation trajectories also changes. For some operation scenarios, the environment scenarios with blockage and obstacles are settled, the GNSS signal is propagated into the receiver through the challenging environment. But when the whole railway track is constructed, the environment scenario and operation scenario is determined. For passenger trains, the time is almost determined. So the GNSS signal reception along the track can be studied in advance to provide a “signal quality map”. This paper aims to explore the collected GNSS signal quality along the railway track to generate a GNSS quality grid map especially for challenging environment for train operation. Firstly, The GNSS satellite elevation and azimuth angle, together with the SNR (signal-to-noise ratio) are studied for cluster analysis to determine the similar pattern of the signal propagation. The SNR measurement is key to distinguish the signal quality to understand the possible propagation trajectory of the signal, in the settled railway track it is possible to characterize the GNSS signal quality in the specific track area. Using the elevation and azimuth angle, the environment blockage can be found and analyzed later using a fish-eye camera. Secondly, the cluster analysis results for the GNSS signal is plotted above a geographical pre-surveyed track map, the challenging environments can be easily found. The GNSS signal quality is generated as quality grid map for accuracy estimation. Finally, the error along the track is estimated using the environment features and signal quality using error allocation methods. A one month measured data-set in the Qinghai-Tibet Railway line from Golmud to Lhasa with 1142 km long GNSS measured train movement data is studied and extracted for cluster analysis. The analyzed results deliver possible challenging and signal degraded environments for GNSS. This provides the guides for train operation scenario settlements along the track for further applications. The results showed the identification of the challenging environment as “half-sky” and “train station”, GNSS signal grid map shows the estimated GNSS SPS (standard positioning service) in the operation environment.