A GPS water vapour tomography method based on a genetic algorithm
Fei Yang,Jiming Guo,Junbo Shi,Xiaolin Meng,Yinzhi Zhao,Lv Zhou,and Di Zhang
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
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
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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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...
