A Zenith Tropospheric Delay Modeling Method Based on the UNB3m Model and Kriging Spatial Interpolation
Tallennettuna:
| Julkaisussa: | Atmosphere vol. 16, no. 8 (2025), p. 921-940 |
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| Muut tekijät: | , , , , |
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MDPI AG
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| Linkit: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 100 | 1 | |a Huineng, Yan |u School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou 341000, China; 9320230047@gnust.edu.cn (H.Y.); 9320240111@gnust.edu.cn (F.L.); liyu@Intu.edu.cn (Y.L.); wangrui@gnust.edu.cn (R.W.) | |
| 245 | 1 | |a A Zenith Tropospheric Delay Modeling Method Based on the UNB3m Model and Kriging Spatial Interpolation | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a To accurately estimate Zenith Tropospheric Delay (ZTD) for high-precision positioning of the Global Navigation Satellite System (GNSS), this study proposes a modeling method of ZTD based on the UNB3m model and Kriging spatial interpolation, in which the optimal spatial interpolation parameters are determined based on the errors corresponding to different combinations of the interpolation parameters, and the spatial distribution of the GNSS modeling stations is determined by the interpolation errors of the randomly selected GNSS stations for several times. To verify the accuracy and reliability of the proposed model, the ZTD estimates of 132,685 epochs with 1 h or 2 h temporal resolution for 28 years from 1997 to 2025 of the global network of continuously operating GNSS tracking stations are used as inputs; the ZTD results at any position and the corresponding observation moment can be obtained with the proposed model. The experimental results show that the model error is less than 30 mm in more than 85% of the observation epochs, the ZTD estimation results are less affected by the horizontal position and height of the GNSS stations than traditional models, and the ZTD interpolation error is improved by 10–40 mm compared to the GPT3 and UNB3m models at the four GNSS checking stations. Therefore, this technology can provide ZTD estimation results for single- and dual-frequency hybrid deformation monitoring, as well as dense ZTD data for Precipitable Water Vapor (PWV) inversion. Since the proposed method has the advantages of simple implementation, high accuracy, high reliability, and ease of promotion, it is expected to be fully applied in other high-precision positioning applications. | |
| 653 | |a Parameters | ||
| 653 | |a Accuracy | ||
| 653 | |a Temporal resolution | ||
| 653 | |a Precipitable water | ||
| 653 | |a Zenith | ||
| 653 | |a Modelling | ||
| 653 | |a Navigation | ||
| 653 | |a Atmospheric pressure | ||
| 653 | |a Water vapor | ||
| 653 | |a Reliability | ||
| 653 | |a Navigation satellites | ||
| 653 | |a Data processing | ||
| 653 | |a Horizontal orientation | ||
| 653 | |a Spatial distribution | ||
| 653 | |a Deformation | ||
| 653 | |a Navigation systems | ||
| 653 | |a Interpolation errors | ||
| 653 | |a Interpolation | ||
| 653 | |a Navigational satellites | ||
| 653 | |a Troposphere | ||
| 653 | |a Methods | ||
| 653 | |a Errors | ||
| 653 | |a Water vapour | ||
| 653 | |a Tracking stations | ||
| 653 | |a Satellites | ||
| 653 | |a Global navigation satellite system | ||
| 653 | |a Parameter estimation | ||
| 700 | 1 | |a Lu, Zhigang |u School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou 341000, China; 9320230047@gnust.edu.cn (H.Y.); 9320240111@gnust.edu.cn (F.L.); liyu@Intu.edu.cn (Y.L.); wangrui@gnust.edu.cn (R.W.) | |
| 700 | 1 | |a Li, Fang |u School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou 341000, China; 9320230047@gnust.edu.cn (H.Y.); 9320240111@gnust.edu.cn (F.L.); liyu@Intu.edu.cn (Y.L.); wangrui@gnust.edu.cn (R.W.) | |
| 700 | 1 | |a Li, Yu |u School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou 341000, China; 9320230047@gnust.edu.cn (H.Y.); 9320240111@gnust.edu.cn (F.L.); liyu@Intu.edu.cn (Y.L.); wangrui@gnust.edu.cn (R.W.) | |
| 700 | 1 | |a Li, Fuping |u Key Laboratory of Ionic Rare Earth Resources and Environment, Ministry of Natural Resources of the People’s Republic of China, Ganzhou 341000, China; lifuping@jxyy.edu.cn | |
| 700 | 1 | |a Wang, Rui |u School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou 341000, China; 9320230047@gnust.edu.cn (H.Y.); 9320240111@gnust.edu.cn (F.L.); liyu@Intu.edu.cn (Y.L.); wangrui@gnust.edu.cn (R.W.) | |
| 773 | 0 | |t Atmosphere |g vol. 16, no. 8 (2025), p. 921-940 | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243981589/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3243981589/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243981589/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |