Troposphere Delay Remote Sensing Using Single GPS Receiver
The most prominent spatially correlated errors in GNSS observations are well known to be atmospheric effects. The ionosphere and troposphere are the two main layers of the atmosphere that cause GNSS observations delay. A linear combination of the dual-frequency data can be used to reduce ionospheric...
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Academic Publication Council - Kuwait University
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ftjengresearch:oai:kuwaitjournals.publicknowledgeproject.org:article/16821 2023-05-15T13:57:57+02:00 Troposphere Delay Remote Sensing Using Single GPS Receiver sedeek, ahmed Mohamed Doma Mostafa Rabah Ahmed Elsayed 2022-08-17 application/pdf https://kuwaitjournals.org/jer/index.php/JER/article/view/16821 https://doi.org/10.36909/jer.16821 eng eng Academic Publication Council - Kuwait University https://kuwaitjournals.org/jer/index.php/JER/article/view/16821/3323 https://kuwaitjournals.org/jer/index.php/JER/article/view/16821 doi:10.36909/jer.16821 Copyright (c) 2022 Journal of Engineering Research Journal of Engineering Research; Online First Articles 2307-1885 2307-1877 10.36909/jer.online info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Petroleum Engineering 2022 ftjengresearch https://doi.org/10.36909/jer.16821 https://doi.org/10.36909/jer.online 2022-08-20T18:06:36Z The most prominent spatially correlated errors in GNSS observations are well known to be atmospheric effects. The ionosphere and troposphere are the two main layers of the atmosphere that cause GNSS observations delay. A linear combination of the dual-frequency data can be used to reduce ionospheric delay. The tropospheric delay, unlike the ionospheric delay, cannot be eliminated using the same methods. The troposphere is primarily associated with GPS. The delay it causes in GPS signal is regarded as one of the primary sources of errors that must be eliminated to determine accurate positions. This paper's main purpose is to develop a new source code that can estimate the effect of tropospheric delay over any GPS station. The tropospheric delay in this proposed code is estimated utilizing sequential least-squares adjustment using a model depending on Niell Mapping Function (NMF). This model, known as the Tropospheric Delay Estimation program, was created in the MATLAB® environment (TDE). This research presents the results of tropospheric delay during DOY 2, 2020 of actual data from ten ground-based IGS stations distributed over Antarctica, China, Canada, Fiji, Russia, Greenland, and Portugal IGS stations worldwide. For validation of the proposed code results, they were compared with troposphere delay results of the International GNSS Service (IGS). Good agreement and high correlation were found between both results. In comparison to IGS, the proposed code's standard deviations range from 0.0000525 m to 0.008154 m, indicating how accurate this study is in terms of agreement of solutions provided by IGS. Finally, an adaptable user interface For GPS users, the MATLAB software can accurately estimate troposphere delay. Article in Journal/Newspaper Antarc* Antarctica Greenland Journal of Engineering Research (Kuwait University) Canada Greenland Journal of Engineering Research |
institution |
Open Polar |
collection |
Journal of Engineering Research (Kuwait University) |
op_collection_id |
ftjengresearch |
language |
English |
description |
The most prominent spatially correlated errors in GNSS observations are well known to be atmospheric effects. The ionosphere and troposphere are the two main layers of the atmosphere that cause GNSS observations delay. A linear combination of the dual-frequency data can be used to reduce ionospheric delay. The tropospheric delay, unlike the ionospheric delay, cannot be eliminated using the same methods. The troposphere is primarily associated with GPS. The delay it causes in GPS signal is regarded as one of the primary sources of errors that must be eliminated to determine accurate positions. This paper's main purpose is to develop a new source code that can estimate the effect of tropospheric delay over any GPS station. The tropospheric delay in this proposed code is estimated utilizing sequential least-squares adjustment using a model depending on Niell Mapping Function (NMF). This model, known as the Tropospheric Delay Estimation program, was created in the MATLAB® environment (TDE). This research presents the results of tropospheric delay during DOY 2, 2020 of actual data from ten ground-based IGS stations distributed over Antarctica, China, Canada, Fiji, Russia, Greenland, and Portugal IGS stations worldwide. For validation of the proposed code results, they were compared with troposphere delay results of the International GNSS Service (IGS). Good agreement and high correlation were found between both results. In comparison to IGS, the proposed code's standard deviations range from 0.0000525 m to 0.008154 m, indicating how accurate this study is in terms of agreement of solutions provided by IGS. Finally, an adaptable user interface For GPS users, the MATLAB software can accurately estimate troposphere delay. |
format |
Article in Journal/Newspaper |
author |
sedeek, ahmed Mohamed Doma Mostafa Rabah Ahmed Elsayed |
spellingShingle |
sedeek, ahmed Mohamed Doma Mostafa Rabah Ahmed Elsayed Troposphere Delay Remote Sensing Using Single GPS Receiver |
author_facet |
sedeek, ahmed Mohamed Doma Mostafa Rabah Ahmed Elsayed |
author_sort |
sedeek, ahmed |
title |
Troposphere Delay Remote Sensing Using Single GPS Receiver |
title_short |
Troposphere Delay Remote Sensing Using Single GPS Receiver |
title_full |
Troposphere Delay Remote Sensing Using Single GPS Receiver |
title_fullStr |
Troposphere Delay Remote Sensing Using Single GPS Receiver |
title_full_unstemmed |
Troposphere Delay Remote Sensing Using Single GPS Receiver |
title_sort |
troposphere delay remote sensing using single gps receiver |
publisher |
Academic Publication Council - Kuwait University |
publishDate |
2022 |
url |
https://kuwaitjournals.org/jer/index.php/JER/article/view/16821 https://doi.org/10.36909/jer.16821 |
geographic |
Canada Greenland |
geographic_facet |
Canada Greenland |
genre |
Antarc* Antarctica Greenland |
genre_facet |
Antarc* Antarctica Greenland |
op_source |
Journal of Engineering Research; Online First Articles 2307-1885 2307-1877 10.36909/jer.online |
op_relation |
https://kuwaitjournals.org/jer/index.php/JER/article/view/16821/3323 https://kuwaitjournals.org/jer/index.php/JER/article/view/16821 doi:10.36909/jer.16821 |
op_rights |
Copyright (c) 2022 Journal of Engineering Research |
op_doi |
https://doi.org/10.36909/jer.16821 https://doi.org/10.36909/jer.online |
container_title |
Journal of Engineering Research |
_version_ |
1766265900252528640 |