GNSS plays a strategic role on the introduction of the Virtual Balise functionality and the train integrity. Thanks to GNSS, it could be possible to realize cost-effective solutions to increase the safety in the regional lines, where the traffic density is lower. The train position estimation is implemented taking into account that the train is constrained to lie on the track (i.e. track constraint). In this way, we can express the position in terms of the curvilinear abscissa (progressive mileage) of the track corresponding to the train position. However, the impact of local effects such as multipath, foliage attenuation and shadowing in the railway environment plays a crucial role due to the presence of infrastructures like platform roofs, side walls, tunnel entrances, buildings and so on close to the trackside. In the paper, we analyse the impact of those threats on the train GNSSbased position estimation performance. At this aim, several scenarios have been generated by using both real data acquired on a railway test-bed in Sardinia, and synthetic data generated in the lab through ad hoc multipath and foliage models. A sensitivity analysis has been conducted, varying main scenarios parameters (e.g. height of obstacles, presence of trees and shadowing). The result of the performed analysis, in terms of availability, accuracy and integrity, are here presented. mitigations implemented by the ERTMS at system level are not considered since the attention is focused on GNSS only.
This paper presents an innovative global navigation satellite system (GNSS) fault detection and exclusion approach for the adoption of satellite localization in the rail sector. Current global integrity monitoring systems cannot guarantee the safety level needed for such applications as train control where tolerable hazard rate in the order of 10 −9 /h is required. A new method, named two tiers, enabling to integrate local augmentation systems and global augmentation infrastructures, is presented. It is based on the comparison of single differences residuals among satellites for detecting signal in space (SIS) faults and double difference residuals among local augmentation stations and satellite-based augmentation systems ranging and integrity monitoring stations for detecting reference stations faults. GPS SIS faults described in literature and real GNSS raw data recorded on a train are taken into account. This study reports the performance analysis for the two-tiers approach carried out during relevant European projects. A test-bed architecture has been developed through the implementa-
In recent years, Global Navigation Satellite System (GNSS) technologies, which take full advantage of both real-time kinematic (RTK) and precise point positioning (PPP), managed to reach centimeter-level positioning accuracy with ambiguity resolution (AR) quick convergence techniques. One great advantage over traditional structural health monitoring (SHM) systems is that GNSS technologies will be functional in disaster management situations, when terrestrial communication links become unavailable. In this study, a multi-GNSS system, based on GPS and Galileo constellations and exploiting advanced RTK and PPP-AR technologies with update rate of 100 Hz is tested on two benchmark structures as an SHM system. The first case study served as a baseline to outline the methodology: first, a setup phase of the instrumentation, then a signal processing phase and last, the validation of the results. The methodology was then applied to a real-case scenario, in which the GNSS was tested on a road bridge. A comparative analysis with the results acquired by a set of accelerometers showed that the GNSS was able to identify the crossing of heavy vehicles. The work is paving the way for the development of an affordable and efficient multi-GNSS-based tool for the monitoring of civil infrastructures.
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