Title: Railways Augmented Multisensor Positioning System
Author(s): Alessandro Neri, Andrea Coluccia, Enrico De Marinis, Claudia Facchinetti, Paola Madonna, Michele Mascolo, Federica Pascucci, Pietro Salvatori, Luca Sfarzo, Alberto Tuozzi
Published in: Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
Portland, Oregon
Pages: 2924 - 2943
Cite this article: Neri, Alessandro, Coluccia, Andrea, De Marinis, Enrico, Facchinetti, Claudia, Madonna, Paola, Mascolo, Michele, Pascucci, Federica, Salvatori, Pietro, Sfarzo, Luca, Tuozzi, Alberto, "Railways Augmented Multisensor Positioning System," Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 2924-2943.
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Abstract: The aim of this work is the description of a prototype of rail application that combines multiple GNSS-based technologies, PPP algorithm and multi-sensor fusion between low-cost IMU and GNSS. This prototype is suitable for high demanding safety applications and is developed under the framework of the RAMPS (Railways Augmented Multi-sensor Positioning System) project, co-funded by ASI, the Italian Space Agency. The project team is made up by TRS Sistemi s.r.l. (as prime), the Engineering Department of the University of Roma TRE (MCIP Lab and COMLab), DUNE s.r.l. (as partners) and Radiolabs consortium as subcontractor of some activities. It is some years now that the use of GNSS technology in the railway domain is receiving more and more focus, thanks to the possibility of cost reduction, without penalizing the safety level. The use of a PPP technique, combined with the a-priori knowledge of the track and high integrity algorithms, has shown promising results in terms of accuracy and integrity. To provide a better resilience against strong multipath and to increase the system availability when the sky is partially (or even totally) obstructed, the augmentation with IMU sensor has been introduced. The data fusion has been implemented by an extended complementary Kalman filter, following a loosely coupled approach. To assess the performances of the prototype, a virtualized testbed has been developed, including both a satellite simulator (for the generation of SISs of constellations that have not yet been fully deployed) and a train simulator, modelling the train dynamics and the IMU sensing, fully synchronized with the GNSS component. To characterize the real environment, so to reproduce a realistic scenario, GNSS and IMU observations collected during a trial campaign have been employed. The GNSS emulator is also able to provide the data (i.e. precise ephemeris and satellite clocks data) required to perform a PPP approach and to model the impairments affecting the observations (e.g. multipath effect, satellite faults and cycle slips).