Development and evaluation of the refined zenith tropospheric delay (ZTD) models
Abstract The tropospheric delay is a significant error source in Global Navigation Satellite System (GNSS) positioning and navigation. It is usually projected into zenith direction by using a mapping function. It is particularly important to establish a model that can provide stable and accurate Zen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-10-01
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| Series: | Satellite Navigation |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43020-021-00052-0 |
| _version_ | 1818930248450834432 |
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| author | Fei Yang Xiaolin Meng Jiming Guo Debao Yuan Ming Chen |
| author_facet | Fei Yang Xiaolin Meng Jiming Guo Debao Yuan Ming Chen |
| author_sort | Fei Yang |
| collection | DOAJ |
| description | Abstract The tropospheric delay is a significant error source in Global Navigation Satellite System (GNSS) positioning and navigation. It is usually projected into zenith direction by using a mapping function. It is particularly important to establish a model that can provide stable and accurate Zenith Tropospheric Delay (ZTD). Because of the regional accuracy difference and poor stability of the traditional ZTD models, this paper proposed two methods to refine the Hopfield and Saastamoinen ZTD models. One is by adding annual and semi-annual periodic terms and the other is based on Back-Propagation Artificial Neutral Network (BP-ANN). Using 5-year data from 2011 to 2015 collected at 67 GNSS reference stations in China and its surrounding regions, the four refined models were constructed. The tropospheric products at these GNSS stations were derived from the site-wise Vienna Mapping Function 1 (VMP1). The spatial analysis, temporal analysis, and residual distribution analysis for all the six models were conducted using the data from 2016 to 2017. The results show that the refined models can effectively improve the accuracy compared with the traditional models. For the Hopfield model, the improvement for the Root Mean Square Error (RMSE) and bias reached 24.5/49.7 and 34.0/52.8 mm, respectively. These values became 8.8/26.7 and 14.7/28.8 mm when the Saastamoinen model was refined using the two methods. This exploration is conducive to GNSS navigation and positioning and GNSS meteorology by providing more accurate tropospheric prior information. |
| first_indexed | 2024-12-20T03:57:41Z |
| format | Article |
| id | doaj.art-2a15ab3684704de3bfb40fe40ce09626 |
| institution | Directory Open Access Journal |
| issn | 2662-1363 |
| language | English |
| last_indexed | 2024-12-20T03:57:41Z |
| publishDate | 2021-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Satellite Navigation |
| spelling | doaj.art-2a15ab3684704de3bfb40fe40ce096262022-12-21T19:54:15ZengSpringerOpenSatellite Navigation2662-13632021-10-01211910.1186/s43020-021-00052-0Development and evaluation of the refined zenith tropospheric delay (ZTD) modelsFei Yang0Xiaolin Meng1Jiming Guo2Debao Yuan3Ming Chen4College of Geoscience and Surveying Engineering, China University of Mining and Technology-BeijingGlobal Geospatial Engineering Ltd., The Sino-UK Geospatial Engineering CentreSchool of Geodesy and Geomatics, Wuhan UniversityCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-BeijingNational Geomatics Center of ChinaAbstract The tropospheric delay is a significant error source in Global Navigation Satellite System (GNSS) positioning and navigation. It is usually projected into zenith direction by using a mapping function. It is particularly important to establish a model that can provide stable and accurate Zenith Tropospheric Delay (ZTD). Because of the regional accuracy difference and poor stability of the traditional ZTD models, this paper proposed two methods to refine the Hopfield and Saastamoinen ZTD models. One is by adding annual and semi-annual periodic terms and the other is based on Back-Propagation Artificial Neutral Network (BP-ANN). Using 5-year data from 2011 to 2015 collected at 67 GNSS reference stations in China and its surrounding regions, the four refined models were constructed. The tropospheric products at these GNSS stations were derived from the site-wise Vienna Mapping Function 1 (VMP1). The spatial analysis, temporal analysis, and residual distribution analysis for all the six models were conducted using the data from 2016 to 2017. The results show that the refined models can effectively improve the accuracy compared with the traditional models. For the Hopfield model, the improvement for the Root Mean Square Error (RMSE) and bias reached 24.5/49.7 and 34.0/52.8 mm, respectively. These values became 8.8/26.7 and 14.7/28.8 mm when the Saastamoinen model was refined using the two methods. This exploration is conducive to GNSS navigation and positioning and GNSS meteorology by providing more accurate tropospheric prior information.https://doi.org/10.1186/s43020-021-00052-0GNSSTropospheric delayZTDRefined modelANN |
| spellingShingle | Fei Yang Xiaolin Meng Jiming Guo Debao Yuan Ming Chen Development and evaluation of the refined zenith tropospheric delay (ZTD) models Satellite Navigation GNSS Tropospheric delay ZTD Refined model ANN |
| title | Development and evaluation of the refined zenith tropospheric delay (ZTD) models |
| title_full | Development and evaluation of the refined zenith tropospheric delay (ZTD) models |
| title_fullStr | Development and evaluation of the refined zenith tropospheric delay (ZTD) models |
| title_full_unstemmed | Development and evaluation of the refined zenith tropospheric delay (ZTD) models |
| title_short | Development and evaluation of the refined zenith tropospheric delay (ZTD) models |
| title_sort | development and evaluation of the refined zenith tropospheric delay ztd models |
| topic | GNSS Tropospheric delay ZTD Refined model ANN |
| url | https://doi.org/10.1186/s43020-021-00052-0 |
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