Analysis and Empirical Modeling of Ionospheric Horizontal Gradients in the TEC Mapping Onboard LEO Satellites

Wu, Mengjie; Guo, Peng; Xue, Junchen; Wang, Yanguang; Tian, Ye; Wu, Jianming

doi:10.1109/tgrs.2022.3188336

Cited by 2 publications

(2 citation statements)

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“…In addition, accurate plasmasphere information has a potential role in the ionospheric delay correction of precise GNSS positioning applications [32][33][34]. Wen et al pointed out that the limitation of the commonly used single-layer mapping function can be attributed to its neglecting the electron content contributed by the plasmasphere [32].…”

Section: Introductionmentioning

confidence: 99%

“…Lyu et al developed a two-layer mapping function, namely, BIMF, to achieve more accurate vertical-slant TEC conversion when using high-precision VTEC products, and the reason for the success of BIMF model is precisely because it takes the plasmasphere information into account [33]. Wu et al investigated the horizontal gradients of the plasmasphere and proposed a mapping function for LEO satellites by parametrizing the time, location, elevation, and azimuth angle-based horizontal gradients using the global core plasma model (GCPM) [34]. However, there have been no reports related to the applications of an empirical PEC model in ionospheric delay error mitigation yet.…”

Section: Introductionmentioning

confidence: 99%

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An EOF-Based Global Plasmaspheric Electron Content Model and Its Potential Role in Vertical-Slant TEC Conversion

Long,

Gao,

Dong

et al. 2024

Remote Sensing

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Topside total electron content (TEC) data measured by COSMIC/FORMAT-3 during 2008 and 2016 were used to analyze and model the global plasmaspheric electron content (PEC) above 800 km with the help of the empirical orthogonal function (EOF) analysis method, and the potential role of the proposed PEC model in helping Global Navigation Satellite System (GNSS) users derive accurate slant TEC (STEC) from existing high-precision vertical TEC (VTEC) products was validated. A uniform gridded PEC dataset was first obtained using the spherical harmonic regression method, and then, it was decomposed into EOF basis modes. The first four major EOF modes contributed more than 99% of the total variance. They captured the pronounced latitudinal gradient, longitudinal differences, hemispherical differences, diurnal and seasonal variations, and the solar activity dependency of global PEC. A second-layer EOF decomposition was conducted for the spatial pattern and amplitude coefficients of the first-layer EOF modes, and an empirical PEC model was constructed by fitting the second-layer basis functions related to latitude, longitude, local time, season, and solar flux. The PEC model was designed to be driven by whether solar proxy or parameters derived from the Klobuchar model meet the real-time requirements. The validation of the results demonstrated that the proposed PEC model could accurately simulate the major spatiotemporal patterns of global PEC, with a root-mean-square (RMS) error of 1.53 and 2.24 TECU, improvements of 40.70% and 51.74% compared with NeQuick2 model in 2009 and 2014, respectively. Finally, the proposed PEC model was applied to conduct a vertical-slant TEC conversion experiment with high-precision Global Ionospheric Maps (GIMs) and dual-frequency carrier phase observables of more than 400 globally distributed GNSS sites. The results of the differential STEC (dSTEC) analysis demonstrated the effectiveness of the proposed PEC model in aiding precise vertical-slant TEC conversion. It improved by 18.52% in dSTEC RMS on a global scale and performed better in 90.20% of the testing days compared with the commonly used single-layer mapping function.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%