A Map Based Multipath Error Model for Safety Critical Navigation in Railway Environments

Abstract

Critical railway systems, like signalling or automatic train control (ATC), are envisioned to rely on satellite-based localization. The safety aspect requires that the localization system does not only provide accurate information but also proper error uncertainty estimation and integrity quantification. This is challenging to be achieved for railway applications, since the environment is very complex and GNSS is typically affected by multiple local threats. In particular, multipath must be carefully modelled. In this work, we present a methodology to obtain a robust multipath error model for GNSS code observations that is adapted to each position along the railway track map. The method relies on the fact that the position of the train is constraint to the tracks and therefore the location specific impact of the environment is repeatable. The error model is therefore obtained and tested in this paper by the accumulation of data over several train runs collected with dedicated real measurement campaigns. The multipath error bounding capability is evaluated by using a modified horizontal ARAIM (H-ARAIM) adapted for the railway environment. Results show that the map-based error model can enable safe error quantification, in particular in challenging scenarios.