An enhanced tropospheric fusion model based on China’s National continuously operating reference stations
This study introduces a multi-source data fusion model of the tropospheric delay over China and uses GNSS data, meteorological data, and Global Pressure and Temperature 2 wet (GPT2w) model data to derive the model coefficients. Fifty-one nationwide GNSS stations were selected to evaluate the accurac...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-01-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2446309 |
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| Summary: | This study introduces a multi-source data fusion model of the tropospheric delay over China and uses GNSS data, meteorological data, and Global Pressure and Temperature 2 wet (GPT2w) model data to derive the model coefficients. Fifty-one nationwide GNSS stations were selected to evaluate the accuracy of the fusion model through a detailed analysis of the model performance based on factors including the overall accuracy, seasonal accuracy, and impact of the station location. The results show that the multi-source data fusion model integrates the advantages of various individual models and thus has a higher accuracy and stability despite the occurrence of a certain degree of decline in accuracy in the individual models under certain conditions. A comparison with previous models developed using only GNSS data demonstrates that this fusion model improves the overall accuracy by 17.7%. |
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| ISSN: | 1009-5020 1993-5153 |