Impact of robot antenna calibration on dual-frequency smartphone-based high-accuracy positioning: a case study using the Huawei Mate20X

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Darugna, F.; Wübbena, J.B.; Wübbena, G.; Schmitz, M.; Schön, S.; Warneke, A.; Impact of robot antenna calibration on dual-frequency smartphone-based high-accuracy positioning: a case study using the Huawei Mate20X. In: GPS Solutions 25 (2021), 15. DOI: https://doi.org/10.1007/s10291-020-01048-0

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10307

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Sum total of downloads: 33




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Abstract: 
The access to Android-based Global Navigation Satellite Systems (GNSS) raw measurements has become a strong motivation to investigate the feasibility of smartphone-based positioning. Since the beginning of this research, the smartphone GNSS antenna has been recognized as one of the main limitations. Besides multipath (MP), the radiation pattern of the antenna is the main site-dependent error source of GNSS observations. An absolute antenna calibration has been performed for the dual-frequency Huawei Mate20X. Antenna phase center offset (PCO) and variations (PCV) have been estimated to correct for antenna impact on the L1 and L5 phase observations. Accordingly, we show the relevance of considering the individual PCO and PCV for the two frequencies. The PCV patterns indicate absolute values up to 2 cm and 4 cm for L1 and L5, respectively. The impact of antenna corrections has been assessed in different multipath environments using a high-accuracy positioning algorithm employing an undifferenced observation model and applying ambiguity resolution. Successful ambiguity resolution is shown for a smartphone placed in a low multipath environment on the ground of a soccer field. For a rooftop open-sky test case with large multipath, ambiguity resolution was successful in 19 out of 35 data sets. Overall, the antenna calibration is demonstrated being an asset for smartphone-based positioning with ambiguity resolution, showing cm-level 2D root mean square error (RMSE).
License of this version: CC BY 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 16 48.48%
2 image of flag of China China 5 15.15%
3 image of flag of United Kingdom United Kingdom 4 12.12%
4 image of flag of Belgium Belgium 4 12.12%
5 image of flag of United States United States 2 6.06%
6 image of flag of India India 1 3.03%
7 image of flag of Switzerland Switzerland 1 3.03%

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