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

Radiolabs presents the RHINOS project at InnoTrans 2016

Category: Events Created: Tuesday, 20 September 2016

Radiolabs, will be showcase RHINOS research project at InnoTrans – the leading international trade fair on Railways transport technologies and products that will take place by 20th to 23th September in Berlin, Germany. 

RHINOS, an H2020 GSA Galileo 3 project, aims to exploit GNSS infrastructures by developing augmentation techniques to achieve high integrity train localization to be used for train control systems on a world-wide basis. The consortium, led by Radiolabs involves major international research centers on GNSS as DLR in Germany, Nottingham University in UK, Stanford University in the USA and Pardubice University in Check Republic putting together a team of more than 30 experts on GNSS. The RHINOS presentation will be available at the GSA Stand.



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