Details
Original language | English |
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Title of host publication | 2022 IEEE Intelligent Vehicles Symposium (IV) |
Pages | 1774-1781 |
Number of pages | 8 |
ISBN (electronic) | 978-1-6654-8821-1 |
Publication status | Published - 2022 |
Event | 2022 IEEE Intelligent Vehicles Symposium (IV 2022) - Eurocongress Aachen, Aachen, Germany Duration: 5 Jun 2022 → 9 Jun 2022 https://ieeexplore.ieee.org/xpl/conhome/1000397/all-proceedings |
Publication series
Name | IEEE Intelligent Vehicles Symposium, Proceedings |
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Volume | 2022-June |
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.
ASJC Scopus subject areas
- Engineering(all)
- Mathematics(all)
- Applied Mathematics
Research Area (based on ÖFOS 2012)
- TECHNICAL SCIENCES
- Environmental Engineering, Applied Geosciences
- Geodesy, Surveying
- Geodesy
- TECHNICAL SCIENCES
- Environmental Engineering, Applied Geosciences
- Geodesy, Surveying
- Navigation systems
Sustainable Development Goals
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2022 IEEE Intelligent Vehicles Symposium (IV). 2022. p. 1774-1781 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2022-June).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Towards Integrity for GNSS-based urban navigation
T2 - 2022 IEEE Intelligent Vehicles Symposium (IV 2022)
AU - Schön, Steffen
AU - Baasch, Kai-niklas
AU - Icking, Lucy
AU - Karimidoona, Ali
AU - Lin, Qianwen
AU - Ruwisch, Fabian
AU - Schaper, Anat
AU - Su, Jingyao
N1 - 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 TÜV-Rheinland (PT-TÜV) 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.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85135378243&partnerID=8YFLogxK
U2 - 10.1109/IV51971.2022.9827402
DO - 10.1109/IV51971.2022.9827402
M3 - Conference contribution
SN - 978-1-6654-8822-8
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 1774
EP - 1781
BT - 2022 IEEE Intelligent Vehicles Symposium (IV)
Y2 - 5 June 2022 through 9 June 2022
ER -