Articles | Volume 13, issue 1
https://doi.org/10.5194/amt-13-355-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-355-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Jan 2020
Research article |
| 31 Jan 2020
| 31 Jan 2020
A GPS water vapour tomography method based on a genetic algorithm
Fei Yang
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079,
China
Nottingham Geospatial Institute, University of Nottingham, Nottingham
NG7 2TU, UK
Key Laboratory of Precise Engineering and Industry Surveying of
National Administration of Surveying, Mapping and Geoinformation, Wuhan
University, Wuhan 430079, China
Research Center for High Accuracy Location Awareness, Wuhan
University, China
Jiming Guo
CORRESPONDING AUTHOR
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079,
China
Key Laboratory of Precise Engineering and Industry Surveying of
National Administration of Surveying, Mapping and Geoinformation, Wuhan
University, Wuhan 430079, China
Research Center for High Accuracy Location Awareness, Wuhan
University, China
Junbo Shi
CORRESPONDING AUTHOR
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079,
China
Key Laboratory of Precise Engineering and Industry Surveying of
National Administration of Surveying, Mapping and Geoinformation, Wuhan
University, Wuhan 430079, China
Xiaolin Meng
Nottingham Geospatial Institute, University of Nottingham, Nottingham
NG7 2TU, UK
Yinzhi Zhao
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079,
China
Lv Zhou
Guilin University of Technology, Guilin 541004, China
Di Zhang
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079,
China
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Cited
12 citations as recorded by crossref.
- Generation of 3D water vapour tomography using voxel-based approach in the Himalayan region A. Srivastava 10.1007/s12040-024-02293-4
- Assessment of tomographic window and sampling rate effects on GNSS water vapor tomography F. Yang et al. 10.1186/s43020-023-00096-4
- GNSS ground-based tomography: state-of-the-art and technological challenges S. Saxena & R. Dwivedi 10.1080/01431161.2023.2247526
- Evaluation of the weighted mean temperature over China using multiple reanalysis data and radiosonde Y. Sun et al. 10.1016/j.atmosres.2023.106664
- GNSS water vapor tomography based on Kalman filter with optimized noise covariance F. Yang et al. 10.1007/s10291-023-01517-2
- A virtual-signal method for enhancing the efficacy of GNSS tropospheric tomography using artificial neural network technique M. Zhang et al. 10.1007/s10291-025-01935-4
- An Improved Tropospheric Tomographic Model Based on Artificial Neural Network M. Zhang et al. 10.1109/JSTARS.2023.3278302
- From GNSS Zenith Tropospheric Delay to Precipitable Water Vapor: Accuracy Assessment Using In-Situ and Reanalysis Meteorological Data Over China H. Wang et al. 10.1109/JSTARS.2025.3569930
- Development of an adaptive 4-D water vapour density model for the vertical constraints in GNSS tropospheric tomography M. Zhang et al. 10.1007/s10291-024-01700-z
- Atmospheric Water Vapor Variability over Houston: Continuous GNSS Tomography in the Year of Hurricane Harvey (2017) P. Mateus et al. 10.3390/rs16173205
- Assessment of the Water Vapor Tomography Based on Four Navigation Satellite Systems and Their Various Combinations F. Yang et al. 10.3390/rs14153552
- Adaptive Voxel-Division Method of GNSS Water Vapor Tomography and Its Application in Data Assimilation Y. Ma et al. 10.1109/JSTARS.2025.3580555
12 citations as recorded by crossref.
- Generation of 3D water vapour tomography using voxel-based approach in the Himalayan region A. Srivastava 10.1007/s12040-024-02293-4
- Assessment of tomographic window and sampling rate effects on GNSS water vapor tomography F. Yang et al. 10.1186/s43020-023-00096-4
- GNSS ground-based tomography: state-of-the-art and technological challenges S. Saxena & R. Dwivedi 10.1080/01431161.2023.2247526
- Evaluation of the weighted mean temperature over China using multiple reanalysis data and radiosonde Y. Sun et al. 10.1016/j.atmosres.2023.106664
- GNSS water vapor tomography based on Kalman filter with optimized noise covariance F. Yang et al. 10.1007/s10291-023-01517-2
- A virtual-signal method for enhancing the efficacy of GNSS tropospheric tomography using artificial neural network technique M. Zhang et al. 10.1007/s10291-025-01935-4
- An Improved Tropospheric Tomographic Model Based on Artificial Neural Network M. Zhang et al. 10.1109/JSTARS.2023.3278302
- From GNSS Zenith Tropospheric Delay to Precipitable Water Vapor: Accuracy Assessment Using In-Situ and Reanalysis Meteorological Data Over China H. Wang et al. 10.1109/JSTARS.2025.3569930
- Development of an adaptive 4-D water vapour density model for the vertical constraints in GNSS tropospheric tomography M. Zhang et al. 10.1007/s10291-024-01700-z
- Atmospheric Water Vapor Variability over Houston: Continuous GNSS Tomography in the Year of Hurricane Harvey (2017) P. Mateus et al. 10.3390/rs16173205
- Assessment of the Water Vapor Tomography Based on Four Navigation Satellite Systems and Their Various Combinations F. Yang et al. 10.3390/rs14153552
- Adaptive Voxel-Division Method of GNSS Water Vapor Tomography and Its Application in Data Assimilation Y. Ma et al. 10.1109/JSTARS.2025.3580555
Latest update: 15 Sep 2025
Short summary
The development of GPS station networks that provide rich data sources containing atmospheric information will enable more GPS applications in the field of meteorology. This study describes a genetic algorithm for the water vapour tomography; overcomes the ill-conditioned problem; and eliminates the reliance on excessive constraints, priori information, and external data. It is proven in the paper that accurate 3-D water vapour distribution can be provided by this study for atmospheric research.
The development of GPS station networks that provide rich data sources containing atmospheric...
