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Session B5: Atmospheric Science and Space Applications

Spatial-temporal Correlation Analysis of Ionospheric Delay in China based on iGMAS
Zhipeng Wang, Sikun Wang, Wei Shao, Beihang University, China; Qian Sun, China Waterborne Transport Research Institute, China
Location: Grand Ballroom F
Date/Time: Thursday, Feb. 1, 3:35 p.m.

Peer Reviewed

Ionospheric delay is one of the most significant sources of GNSS ranging error, and ionosphere behaves differently at different latitudes. Currently, America and European countries have conducted extensive researches on ionospheric delay, and established ionospheric delay model for mid-latitudes. However, China is located in middle and low latitude regions. Therefore, the existing ionospheric delay model may not be suitable for China. Ionosphere is the variable of space and time. Spatial-temporal correlation is an important factor affecting the ionosphere research and construction of the local augmentation system. The temporal change rate of ionospheric delay directly influences the update rate of the ionosphere correction, and its spatial change rate restricts the application scope of the differential system. However, existing research lacks further study on spatial-temporal correlation of ionosphere. Therefore, this paper focuses on the spatial-temporal correlation of ionospheric delay in China to carry out the research. International GNSS Monitoring & Assessment System (iGMAS) is a ground monitoring system independently developed by China, which can basically monitor the whole China and provide GNSS observations. This paper presents the spatial-temporal correlation analysis of ionospheric vertical delay in China. First, we explore the method to extract GPS dual-frequency data from iGMAS and obtain precise estimation of ionospheric vertical delay. Based on the statistics of different reference stations’ results, the spatial-temporal characteristics of ionospheric vertical delay are qualitatively summarized, taking the maximum and average values of ionospheric vertical delay as an example. Results show that with the increase of latitudes, ionospheric vertical delay decreases and the seasonal variation is that the ionospheric vertical delay in spring larger than that in autumn and larger than that in summer and winter. Then, we express ionospheric vertical delay model as a trend term and a random term to separate random term, which is spatial-temporal correlated. Finally, the spatial-temporal variogram is achieved to quantitatively analyze spatial-temporal correlation of ionospheric vertical delay in China. Results show that the range of spatial variogram and temporal variogram are 1268 km and 608 s, which means that ionospheric vertical delay within this distance and time interval will have a strong spatial-temporal correlation. This conclusion has important theoretical guidance and engineering value for the research of the ionosphere above China, the construction of GNSS augmentation system and the design of system performance algorithm.



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