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

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Baasch, K.-N.; Icking, L.; Ruwisch, F.; Schoen, S.: Coordinate Frames and Transformations in GNSS Ray-Tracing for Autonomous Driving in Urban Areas. In: Remote sensing 15 (2023), Nr. 1, 180. DOI: https://doi.org/10.3390/rs15010180

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/13400

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Sum total of downloads: 142




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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.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 58 40.85%
2 image of flag of United States United States 19 13.38%
3 image of flag of Russian Federation Russian Federation 16 11.27%
4 image of flag of France France 7 4.93%
5 image of flag of Vietnam Vietnam 4 2.82%
6 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 4 2.82%
7 image of flag of Czech Republic Czech Republic 4 2.82%
8 image of flag of Lithuania Lithuania 3 2.11%
9 image of flag of Hungary Hungary 2 1.41%
10 image of flag of Cameroon Cameroon 2 1.41%
    other countries 23 16.20%

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