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PERFORMANCE EVALUATION OF GNSS FOR TRAIN LOCALIZATION
ABSTRACT
Global Navigation Satellite Systems (GNSS) are applicable to deliver train locations in
real time. This train localization function should comply with railway functional safety
standards; thus, the GNSS performance needs to be evaluated in consistent with railway EN
50126 standard [Reliability, Availability, Maintainability, and Safety (RAMS)]. This paper
demonstrates the performance of the GNSS receiver for train localization. First, the GNSS
performance and railway RAMS properties are compared by definitions. Second, the GNSS
receiver measurements are categorized into three states (i.e., up, degraded, and faulty states). The
relations between the states are illustrated in a stochastic Petri net model. Finally, the
performance properties are evaluated using real data collected on the railway track in High Tatra
Mountains in Slovakia. The property evaluation is based on the definitions represented by the
modeled states.

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Performance evaluation of gnss for train localization

  • 1. PERFORMANCE EVALUATION OF GNSS FOR TRAIN LOCALIZATION ABSTRACT Global Navigation Satellite Systems (GNSS) are applicable to deliver train locations in real time. This train localization function should comply with railway functional safety standards; thus, the GNSS performance needs to be evaluated in consistent with railway EN 50126 standard [Reliability, Availability, Maintainability, and Safety (RAMS)]. This paper demonstrates the performance of the GNSS receiver for train localization. First, the GNSS performance and railway RAMS properties are compared by definitions. Second, the GNSS receiver measurements are categorized into three states (i.e., up, degraded, and faulty states). The relations between the states are illustrated in a stochastic Petri net model. Finally, the performance properties are evaluated using real data collected on the railway track in High Tatra Mountains in Slovakia. The property evaluation is based on the definitions represented by the modeled states.