Low-latency GNSS multipath simulation and building wall detection in urban environments

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

Externe Organisationen

  • Geo++ GmbH
  • Robert Bosch GmbH
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)71-89
Seitenumfang19
FachzeitschriftSimulation
Jahrgang100
Ausgabenummer1
Frühes Online-Datum2023
PublikationsstatusVeröffentlicht - Jan. 2024

Abstract

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 61multipath 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.

ASJC Scopus Sachgebiete

Zitieren

Low-latency GNSS multipath simulation and building wall detection in urban environments. / O’Connor, Marcus; Kersten, Tobias; Skupin, Christian et al.
in: Simulation, Jahrgang 100, Nr. 1, 01.2024, S. 71-89.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

O’Connor M, Kersten T, Skupin C, Ruwisch F, Ren L, Wübbena T et al. Low-latency GNSS multipath simulation and building wall detection in urban environments. Simulation. 2024 Jan;100(1):71-89. Epub 2023. doi: 10.1177/00375497221145601
O’Connor, Marcus ; Kersten, Tobias ; Skupin, Christian et al. / Low-latency GNSS multipath simulation and building wall detection in urban environments. in: Simulation. 2024 ; Jahrgang 100, Nr. 1. S. 71-89.
Download
@article{ac9f572b35b3492bb11c722dd0279f83,
title = "Low-latency GNSS multipath simulation and building wall detection in urban environments",
abstract = "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{\textquoteright}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.",
keywords = "GPGPU, Real-time simulation, city GML, multipath, ray tracing, urban GNSS positioning",
author = "Marcus O{\textquoteright}Connor and Tobias Kersten and Christian Skupin and Fabian Ruwisch and Le Ren and Temmo W{\"u}bbena and Steffen Sch{\"o}n",
note = "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 T{\"U}V-Rheinland (PT-T{\"U}V) under the grants 19A20002A-C. ",
year = "2024",
month = jan,
doi = "10.1177/00375497221145601",
language = "English",
volume = "100",
pages = "71--89",
journal = "Simulation",
issn = "0037-5497",
publisher = "SAGE Publications Ltd",
number = "1",

}

Download

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 -