Towards Integrity for GNSS-based urban navigation

challenges and lessons learned

authored by: Steffen Schön, Kai-niklas Baasch, Lucy Icking, Ali Karimidoona, Qianwen Lin, Fabian Ruwisch, Anat Schaper, Jingyao Su
Abstract: For safety critical applications like autonomous driving, high trust in the reported navigation solution is mandatory. This trust can be expressed by the navigation performance parameters, especially integrity. Multipath errors are the most challenging error source in GNSS since only partial correction is possible. In order to ensure high integrity of GNSS-based urban navigation, signal propagation mechanisms and the potential error sources induced by the complex measurement environment should be sufficiently understood. In this contribution, we report on recent progress on this topic in our group. We conducted various experiments in urban areas and investigated the behavior and magnitude of GNSS signal propagation errors. To this end, ray tracing algorithms combined with 3D city models are implemented to identify propagation obstructions and quantity propagation errors. A Fresnel zone-based criterion is exploited to determine the occurrence and magnitude of diffraction. GNSS Feature Maps are proposed to visualize the analyses and to predict situations with potential loss of integrity. To measure the integrity of urban navigation, we developed alternative set-based approaches in addition to the classical stochastic approach. Based on interval mathematics and geometrical constraints, they are sufficient to bound remaining systematic uncertainty and feasible for integrity applications.
Organisation(s): Institute of Geodesy
Faculty of Civil Engineering and Geodetic Science
Type: Conference contribution
Pages: 1774-1781
No. of pages: 8
Publication date: 2022
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Engineering(all), Applied Mathematics
Research Area (based on ÖFOS 2012): Geodesy, Navigation systems
Sustainable Development Goals: SDG 9 - Industry, Innovation, and Infrastructure
Electronic version(s): https://doi.org/10.1109/IV51971.2022.9827402 (Access: Closed)
: Details in the research portal "Research@Leibniz University"

BibTeX

@inproceedings{7c199eea74f140158bd3b0c9ef55a052,
title = "Towards Integrity for GNSS-based urban navigation: challenges and lessons learned",
abstract = "For safety critical applications like autonomous driving, high trust in the reported navigation solution is mandatory. This trust can be expressed by the navigation performance parameters, especially integrity. Multipath errors are the most challenging error source in GNSS since only partial correction is possible. In order to ensure high integrity of GNSS-based urban navigation, signal propagation mechanisms and the potential error sources induced by the complex measurement environment should be sufficiently understood. In this contribution, we report on recent progress on this topic in our group. We conducted various experiments in urban areas and investigated the behavior and magnitude of GNSS signal propagation errors. To this end, ray tracing algorithms combined with 3D city models are implemented to identify propagation obstructions and quantity propagation errors. A Fresnel zone-based criterion is exploited to determine the occurrence and magnitude of diffraction. GNSS Feature Maps are proposed to visualize the analyses and to predict situations with potential loss of integrity. To measure the integrity of urban navigation, we developed alternative set-based approaches in addition to the classical stochastic approach. Based on interval mathematics and geometrical constraints, they are sufficient to bound remaining systematic uncertainty and feasible for integrity applications.",
author = "Steffen Sch{\"o}n and Kai-niklas Baasch and Lucy Icking and Ali Karimidoona and Qianwen Lin and Fabian Ruwisch and Anat Schaper and Jingyao Su",
note = "Funding Information: *This work was supported by the German Research Foundation (DFG) as part of the Research Training Group Integrity and Collaboration in Dynamic Sensor Networks (i.c.sens) [RTG 2159], the German Academic Exchange Service DAAD, and the project KOMET which is managed by T{\"U}V-Rheinland (PT-T{\"U}V) under the grant 19A20002C and funded by the German Federal Ministry for Economic Affairs and Energy (BMWI), based on a resolution by the German Bundestag. ; 2022 IEEE Intelligent Vehicles Symposium (IV 2022) ; Conference date: 05-06-2022 Through 09-06-2022",
year = "2022",
doi = "10.1109/IV51971.2022.9827402",
language = "English",
isbn = "978-1-6654-8822-8",
series = "IEEE Intelligent Vehicles Symposium, Proceedings",
publisher = "IEEE",
pages = "1774--1781",
booktitle = "2022 IEEE Intelligent Vehicles Symposium (IV)",
url = "https://ieeexplore.ieee.org/xpl/conhome/1000397/all-proceedings",
}