Acta Geodaetica et Cartographica Sinica ›› 2020, Vol. 49 ›› Issue (5): 557-568.doi: 10.11947/j.AGCS.2020.20190113

• Geodesy and Navigation • Previous Articles     Next Articles

A multi-GNSS water vapor tomography method considering boundary incident signals

HU Peng, HUANG Guanwen, ZHANG Qin, YAN Xingyuan, LI Zhe   

  1. College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
  • Received:2019-04-11 Revised:2020-01-05 Published:2020-05-23
  • Supported by:
    The National Key Research and Development Program of China (No. 2018YFC1505102);The National Natural Science Foundation of China (Nos. 41774025;41731066);The Special Fund for Technological Innovation Guidance of Shaanxi Province (No. 2018XNCGG05);The Special Fund for Basic Scientific Research of Central Colleges (No. CHD300102269305);The Grand Projects of the BeiDou-2 System (No. GFZX0301040308)

Abstract: Three-dimensional water vapor distribution information with high spatial and temporal sampling can be obtained all-weather by using GNSS water vapor tomography technology, which has become a major research hotspot in GNSS meteorology. At present, the traditional tomography method based on single navigation system has some shortcomings, such as low utilization rate of observation data and uneven distribution of observation. This paper designs and implements a multi-GNSS water vapor tomography method which takes into account the boundary incident signal. The accuracy of the method is verified by using the observation data of Hong Kong CORS network and radio sounding products. The improvement of the results of water vapor tomography by introducing boundary incident signal and multi-GNSS signal is analyzed in detail. The results show that compared with the traditional GPS tomography method, the proposed water vapor tomography method, which combines the advantages of boundary incident signal and multi-GNSS signal, can obtain more accurate and reliable three-dimensional water vapor information.

Key words: 3D water vapor, tomography, GNSS MET, radiosonde data, boundary incident signals

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