Railway High Integrity Navigation Overlay System

The RHINOS work programme includes the investigation of candidate concepts for the provision of the high integrity needed to protect the detected position of the train, as required by the train control system application. The EGNSS (GPS and GALILEO) plus the SBAS constitute the reference infrastructure that is available worldwide. In addition to that, local augmentation elements, ARAIM techniques and other sensors on the train are the add-on specific assets for mitigating the hazards due to the environmental effects which dominates the rail application.
RHINOS will be developed through an international cooperation with the Stanford University researchers that have been involved in the aviation application since the birth of the GPS. They have indisputable knowledge of the GNSS performance and high-integrity applications. The ambition is a positive step beyond the proliferation of GNSS platforms, mainly tailored for regional applications, in favour of a global solution. RHINOS would release the potential benefits of the EGNSS in the fast growing train signalling market

The RHINOS project has been completed

Category: News & Events Created: Tuesday, 23 January 2018

EGNSS infrastructures and ARAIM technologies play an important role for the adoption of GNSS into Train Control Systems

The  RHINOS team, co-ordinated by Radiolabs,  with  DLR, the Universities of Nottingham, Pardubice, Stanford and with Ansaldo STS and Sogei have successfully completed the project - co-funded by GSA - bringing an important contribution for the adoption of GNSS in the train control application. Final results   verified with simulations and experimental data, demonstrated  that is possible to achieve protection levels in the range of 12 meters along the track and 5 meters for parallel track discrimination,  representing a 60-80% improvement respect to previous results.  An innovative two levels architecture with Advanced Receiver Autonomous Integrity Monitoring (ARAIM) has been developed and simulated  to detect and mitigate the multipath  that is the greatest threat to the viability of GNSS for rail applications. These results are expected to contribute to the process of standardization and certification.


This project has received funding from the European GNSS Agency under the European Union’s Horizon 2020 research and innovation programme under grant agreement No.687399