Coordinate Frames and Transformations in GNSS Ray-Tracing for Autonomous Driving in Urban Areas

verfasst von: Kai Niklas Baasch, Lucy Icking, Fabian Ruwisch, Steffen Schön
Abstract: 3D Mapping-Aided (3DMA) Global Navigation Satellite System (GNSS) is a widely used method to mitigate multipath errors. Various research has been presented which utilizes 3D building model data in conjunction with ray-tracing algorithms to compute and predict satellites’ visibility conditions and compute delays caused by signal reflection. To simulate, model and potentially correct multipath errors in highly dynamic applications, such as, e.g., autonomous driving, the satellite–receiver–reflector geometry has to be known precisely in a common reference frame. Three-dimensional building models are often provided by regional public or private services and the coordinate information is usually given in a coordinate system of a map projection. Inconsistencies in the coordinate frames used to express the satellite and user coordinates, as well as the reflector surfaces, lead to falsely determined multipath errors and, thus, reduce the performance of 3DMA GNSS. This paper aims to provide the needed transformation steps to consider when integrating 3D building model data, user position, and GNSS orbit information. The impact of frame inconsistencies on the computed extra path delay is quantified based on a simulation study in a local 3D building model; they can easily amount to several meters. Differences between the extra path-delay computations in a metric system and a map projection are evaluated and corrections are proposed to both variants depending on the accuracy needs and the intended use.
Organisationseinheit(en): Institut für Erdmessung
Typ: Artikel
Journal: Remote Sensing
Band: 15
Anzahl der Seiten: 17
ISSN: 2072-4292
Publikationsdatum: 01.2023
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Erdkunde und Planetologie (insg.)
Elektronische Version(en): https://doi.org/10.3390/rs15010180 (Zugang: Offen)
: Details im Forschungsportal „Research@Leibniz University“

BibTeX

@article{6e1851384deb40be90eab336bafe1e34,
title = "Coordinate Frames and Transformations in GNSS Ray-Tracing for Autonomous Driving in Urban Areas",
abstract = "3D Mapping-Aided (3DMA) Global Navigation Satellite System (GNSS) is a widely used method to mitigate multipath errors. Various research has been presented which utilizes 3D building model data in conjunction with ray-tracing algorithms to compute and predict satellites{\textquoteright} visibility conditions and compute delays caused by signal reflection. To simulate, model and potentially correct multipath errors in highly dynamic applications, such as, e.g., autonomous driving, the satellite–receiver–reflector geometry has to be known precisely in a common reference frame. Three-dimensional building models are often provided by regional public or private services and the coordinate information is usually given in a coordinate system of a map projection. Inconsistencies in the coordinate frames used to express the satellite and user coordinates, as well as the reflector surfaces, lead to falsely determined multipath errors and, thus, reduce the performance of 3DMA GNSS. This paper aims to provide the needed transformation steps to consider when integrating 3D building model data, user position, and GNSS orbit information. The impact of frame inconsistencies on the computed extra path delay is quantified based on a simulation study in a local 3D building model; they can easily amount to several meters. Differences between the extra path-delay computations in a metric system and a map projection are evaluated and corrections are proposed to both variants depending on the accuracy needs and the intended use.",
keywords = "GNSS, Ray-Tracing, 3D building model, NLOS, Coordinate Frames, Autonomous driving, 3D building model, 3DMA, autonomous driving, coordinate frames, GNSS, NLOS, ray-tracing",
author = "Baasch, {Kai Niklas} and Lucy Icking and Fabian Ruwisch and Steffen Sch{\"o}n",
note = "Funding Information: This work was funded by the German Research Foundation (DFG) as part of the Research Training Group i.c.sens [RTG 2159], the project KOMET, which is managed by T{\"U}V-Rheinland (PT-T{\"U}V) under the grant 19A20002C and is funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK), as well as by the project 5GAPS under the grand 45FGU121_E, which is funded by the German Federal Ministry for Digital and Transport (BMDV) on the basis of a decision by the German Bundestag. The publication of this article was funded by the Open Access Fund of Leibniz Universit{\"a}t Hannover. ",
year = "2023",
month = jan,
doi = "10.3390/rs15010180",
language = "English",
volume = "15",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "1",
}