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High Accuracy High Integrity Train Positioning based on GNSS and Image Processing Integration

Authors :
Michele Brizzi
Luca Pallotta
Agostino Ruggeri
Federica Battisti
Alessandro Neri
Gianluigi Lauro
Sara Baldoni
ION GNSS+ 2021
Neri, A.
Battisti, F.
Baldoni, S.
Brizzi, M.
Pallotta, L.
Ruggeri, A.
Lauro, G.
Source :
Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021).
Publication Year :
2021
Publisher :
Institute of Navigation, 2021.

Abstract

One of the major challenges in the design of high accuracy, high integrity localization procedures for rail applications based on Global Navigation Satellite Systems is represented by the local hazards that cannot be mitigated by resorting to augmentation networks. By fact, combining smoothed code pseudoranges with (differential) carrier phase and/or with Inertial Measurement Unit's outputs is ineffective against multipath low frequency components. These issues can be mitigated by processing images, depth maps and/or pointclouds provided by imaging sensors placed on board. The absolute position of the train can be determined by combining its relative position with respect to georeferenced rail infrastructure elements (e.g., panels, signals, signal gantries) provided by the visual localization processing unit with the landmark absolute position. In addition, the visual input can be exploited for determining on which track the train is located and can be used as complementary odometry source. Moreover, the information provided by the visual localization processing unit can be used to monitor integrity and compute the protection levels. In this contribution we present a localization system that integrates a Global Navigation Satellite System receiver, Inertial Measurement Units, and video sensors (such as monocular and stereo video camera, Time of Flight camera and LIDAR), and has the potential to overcome some of the operational and economical limitations of the current train localization system employed in the European Railway Traffic Management System.

Details

ISSN :
23315954
Database :
OpenAIRE
Journal :
Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021)
Accession number :
edsair.doi.dedup.....5f78638245f3e8f31ccf6e0f921a46dd
Full Text :
https://doi.org/10.33012/2021.17945