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5G Positioning: An Analysis of Early Datasets
Global Navigation Satellite Systems (GNSSs) are nowadays the prevailing technology for positioning and navigation. However, with the roll-out of 5G technology, there is a shift towards ‘hybrid positioning’: indeed, 5G time-of-arrival (ToA) measurements can provide additional ranging for positioning,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675248/ https://www.ncbi.nlm.nih.gov/pubmed/38005611 http://dx.doi.org/10.3390/s23229222 |
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author | Pileggi, Chiara Grec, Florin Catalin Biagi, Ludovico |
author_facet | Pileggi, Chiara Grec, Florin Catalin Biagi, Ludovico |
author_sort | Pileggi, Chiara |
collection | PubMed |
description | Global Navigation Satellite Systems (GNSSs) are nowadays the prevailing technology for positioning and navigation. However, with the roll-out of 5G technology, there is a shift towards ‘hybrid positioning’: indeed, 5G time-of-arrival (ToA) measurements can provide additional ranging for positioning, especially in environments where few GNSS satellites are visible. This work reports a preliminary analysis, the processing, and the results of field measurements collected as part of the GINTO5G project funded by ESA’s EGEP programme. The data used in this project were shared by the European Space Agency (ESA) with the DICA of Politecnico di Milano as part of a collaboration within the ESALab@PoliMi research framework established in 2022 between the two organizations. The ToA data were collected during a real-world measurement campaign and they cover a wide range of user environments, such as indoor areas, outdoor open sky, and outdoor obstructed scenarios. Within the test area, eleven self-made replica 5G base stations were set up. A trolley, carrying a self-made 5G receiver and a data storage unit, was moved along predefined trajectories; the trolley’s accurate trajectories were determined by a total station, which provided benchmark positions. In the present work, the 5G data are processed using the least squares method, testing and comparing different strategies. Therefore, the primary goal is to evaluate algorithms for position determination of a user based on 5G observations, and to empirically assess their accuracy. The results obtained are promising, with positional accuracy ranging from decimeters to a few meters in the worst cases. |
format | Online Article Text |
id | pubmed-10675248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106752482023-11-16 5G Positioning: An Analysis of Early Datasets Pileggi, Chiara Grec, Florin Catalin Biagi, Ludovico Sensors (Basel) Article Global Navigation Satellite Systems (GNSSs) are nowadays the prevailing technology for positioning and navigation. However, with the roll-out of 5G technology, there is a shift towards ‘hybrid positioning’: indeed, 5G time-of-arrival (ToA) measurements can provide additional ranging for positioning, especially in environments where few GNSS satellites are visible. This work reports a preliminary analysis, the processing, and the results of field measurements collected as part of the GINTO5G project funded by ESA’s EGEP programme. The data used in this project were shared by the European Space Agency (ESA) with the DICA of Politecnico di Milano as part of a collaboration within the ESALab@PoliMi research framework established in 2022 between the two organizations. The ToA data were collected during a real-world measurement campaign and they cover a wide range of user environments, such as indoor areas, outdoor open sky, and outdoor obstructed scenarios. Within the test area, eleven self-made replica 5G base stations were set up. A trolley, carrying a self-made 5G receiver and a data storage unit, was moved along predefined trajectories; the trolley’s accurate trajectories were determined by a total station, which provided benchmark positions. In the present work, the 5G data are processed using the least squares method, testing and comparing different strategies. Therefore, the primary goal is to evaluate algorithms for position determination of a user based on 5G observations, and to empirically assess their accuracy. The results obtained are promising, with positional accuracy ranging from decimeters to a few meters in the worst cases. MDPI 2023-11-16 /pmc/articles/PMC10675248/ /pubmed/38005611 http://dx.doi.org/10.3390/s23229222 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pileggi, Chiara Grec, Florin Catalin Biagi, Ludovico 5G Positioning: An Analysis of Early Datasets |
title | 5G Positioning: An Analysis of Early Datasets |
title_full | 5G Positioning: An Analysis of Early Datasets |
title_fullStr | 5G Positioning: An Analysis of Early Datasets |
title_full_unstemmed | 5G Positioning: An Analysis of Early Datasets |
title_short | 5G Positioning: An Analysis of Early Datasets |
title_sort | 5g positioning: an analysis of early datasets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675248/ https://www.ncbi.nlm.nih.gov/pubmed/38005611 http://dx.doi.org/10.3390/s23229222 |
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