Details
| Original language | English |
|---|---|
| Pages (from-to) | 71-89 |
| Number of pages | 19 |
| Journal | Simulation |
| Volume | 100 |
| Issue number | 1 |
| Early online date | 2023 |
| Publication status | Published - Jan 2024 |
Abstract
Keywords
- GPGPU, Real-time simulation, city GML, multipath, ray tracing, urban GNSS positioning
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Mathematics(all)
- Modelling and Simulation
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
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In: Simulation, Vol. 100, No. 1, 01.2024, p. 71-89.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Low-latency GNSS multipath simulation and building wall detection in urban environments
AU - O’Connor, Marcus
AU - Kersten, Tobias
AU - Skupin, Christian
AU - Ruwisch, Fabian
AU - Ren, Le
AU - Wübbena, Temmo
AU - Schön, Steffen
N1 - Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK) based on a resolution of the German Bundestag and supervised by TÜV-Rheinland (PT-TÜV) under the grants 19A20002A-C.
PY - 2024/1
Y1 - 2024/1
N2 - Precise navigation for fully autonomous driving—especially in dense urban areas—requires periodic precise position estimates. Global Navigation Satellite System (GNSS) technology has the potential to provide absolute positioning accuracy at a centimeter level. However, buildings in urban environments cause signal distortions and signal reflections—the so-called multipath—which are the most challenging parts in the GNSS error budget. Hence, we developed a scalable real-time multipath simulator for mitigating potential multipath receptions. The simulator uses three-dimensional (3D) building information, satellite, and user positions. The key drivers of latency are the calculation of reflection, diffraction, and line-of-sight, as well as the response time of the 3D building model database. The memory manager of the graphic processing units (GPUs) in combination with a dedicated load balancer enables fast and efficient multipath analysis. Selected case studies demonstrate the simulator’s potential to significantly improve the position accuracy of the processing engine. The use of the multipath simulator reduces the error in 61% of the error measurements in a stress test scenario to less than half of the non-multipath processing. The scalability of the simulator is demonstrated by combining the multipath simulator with a traffic simulator. Furthermore, we present a novel methodology for the detection of walls using GNSS signals to better account for incomplete or erroneous 3D building information in GNSS signal processing.
AB - Precise navigation for fully autonomous driving—especially in dense urban areas—requires periodic precise position estimates. Global Navigation Satellite System (GNSS) technology has the potential to provide absolute positioning accuracy at a centimeter level. However, buildings in urban environments cause signal distortions and signal reflections—the so-called multipath—which are the most challenging parts in the GNSS error budget. Hence, we developed a scalable real-time multipath simulator for mitigating potential multipath receptions. The simulator uses three-dimensional (3D) building information, satellite, and user positions. The key drivers of latency are the calculation of reflection, diffraction, and line-of-sight, as well as the response time of the 3D building model database. The memory manager of the graphic processing units (GPUs) in combination with a dedicated load balancer enables fast and efficient multipath analysis. Selected case studies demonstrate the simulator’s potential to significantly improve the position accuracy of the processing engine. The use of the multipath simulator reduces the error in 61% of the error measurements in a stress test scenario to less than half of the non-multipath processing. The scalability of the simulator is demonstrated by combining the multipath simulator with a traffic simulator. Furthermore, we present a novel methodology for the detection of walls using GNSS signals to better account for incomplete or erroneous 3D building information in GNSS signal processing.
KW - GPGPU
KW - Real-time simulation
KW - city GML
KW - multipath
KW - ray tracing
KW - urban GNSS positioning
UR - http://www.scopus.com/inward/record.url?scp=85147444366&partnerID=8YFLogxK
U2 - 10.1177/00375497221145601
DO - 10.1177/00375497221145601
M3 - Article
VL - 100
SP - 71
EP - 89
JO - Simulation
JF - Simulation
SN - 0037-5497
IS - 1
ER -