Realistic position error models for GNSS simulation in railway environments

Abstract

The positioning accuracy of a Global Navigation Satellite System (GNSS) varies largely with the changing environmental conditions around the receiver. The accuracy degradation is mainly due to the presence of local threats like multipath, NLOS and interferences. During the train run, with the movement of the train, the environment around the track changes very rapidly, so as the positioning accuracy. In this work, we intend to separately examine and model different error distributions. Such error models can be beneficial to provide a flexible/variable protection level that can help to increase subsequent operations on the track and also for sending warning alerts to the trains if any of them is in the degraded mode to avoid train collisions. We present a methodology to model the position errors that are expected to be representative of the environment around the track. The track errors are characterized by 3 different environments: open-sky, forest and urban/suburban regions, as they are typically present around the track. The position errors are projected into the track frame for its suitability with the railway application. The realistic error models are then developed from the estimated errors at the position level. The results presented here show some Gaussian based distribution that will feed the simulation chain developed in the EU Gate4Rail project.