RT‐FAIRS: Real‐Time Factor‐Adjusted Ionospheric Residual Statistics Approach for Generating Accuracy Information in Global Ionospheric Maps

Abstract Ionospheric delays remain a major error source in Global Navigation Satellite Systems (GNSS). The International GNSS Service (IGS) provides Global Ionospheric Maps (GIMs) that offer vertical total electron content (VTEC) estimates together with RMS maps as accuracy information. While such indicators are routinely available in post‐processed GIMs, real‐time GIMs (RT‐GIMs) still lack a corresponding RMS description of the correction errors. This information is essential for robust and integrity‐driven GNSS positioning in the IGS real‐time service community. We introduce the Real‐Time Factor‐Adjusted Ionospheric Residual Statistics (RT‐FAIRS) approach, which exploits residuals from contributing real‐time GNSS stations and applies adjustment factors that account for the non‐Gaussian characteristics of their error distributions. The method particularly improves estimates in data‐sparse regions, providing conservative but adaptive error bounds. RT‐FAIRS has been operationally implemented at the Chinese Academy of Sciences (CAS) for the routine generation and dissemination of real‐time accuracy information in CAS RT‐GIM products. Validation with differential slant TEC (dSTEC) residuals from independent GNSS stations shows that RMS maps in legacy CAS RT‐GIMs often underestimate GIM errors, whereas RT‐FAIRS yields statistically consistent bounds and substantially stronger correlations with observed variations. Comparisons with post‐processed GIMs further demonstrate that RT‐FAIRS ensures both reliability and responsiveness of the generated real‐time accuracy information. The approach provides a statistically consistent framework for RT‐GIM accuracy information assessment and supports the integrity analysis in real‐time GNSS applications.

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Publication Details

Journal
Space Weather
Published
2026-04-01
DOI
https://doi.org/10.1029/2025sw004769
Primary Topic
GNSS positioning and interference
Type
article
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article

RT‐FAIRS: Real‐Time Factor‐Adjusted Ionospheric Residual Statistics Approach for Generating Accuracy Information in Global Ionospheric Maps

Adam Froń, Andrzej Krankowski, Axel Rülke, Reza Ghoddousi‐Fard et al.
Space Weather
GNSS positioning and interference
article

RT‐FAIRS: Real‐Time Factor‐Adjusted Ionospheric Residual Statistics Approach for Generating Accuracy Information in Global Ionospheric Maps

Adam Froń, Andrzej Krankowski, Axel Rülke, Reza Ghoddousi‐Fard, Zhouyu Zhang, Heng Yang, Ang Liu, Manuel Hernández‐Pajares, Ang Li, Zishen Li
article en

Abstract

Abstract Ionospheric delays remain a major error source in Global Navigation Satellite Systems (GNSS). The International GNSS Service (IGS) provides Global Ionospheric Maps (GIMs) that offer vertical total electron content (VTEC) estimates together with RMS maps as accuracy information. While such indicators are routinely available in post‐processed GIMs, real‐time GIMs (RT‐GIMs) still lack a corresponding RMS description of the correction errors. This information is essential for robust and integrity‐driven GNSS positioning in the IGS real‐time service community. We introduce the Real‐Time Factor‐Adjusted Ionospheric Residual Statistics (RT‐FAIRS) approach, which exploits residuals from contributing real‐time GNSS stations and applies adjustment factors that account for the non‐Gaussian characteristics of their error distributions. The method particularly improves estimates in data‐sparse regions, providing conservative but adaptive error bounds. RT‐FAIRS has been operationally implemented at the Chinese Academy of Sciences (CAS) for the routine generation and dissemination of real‐time accuracy information in CAS RT‐GIM products. Validation with differential slant TEC (dSTEC) residuals from independent GNSS stations shows that RMS maps in legacy CAS RT‐GIMs often underestimate GIM errors, whereas RT‐FAIRS yields statistically consistent bounds and substantially stronger correlations with observed variations. Comparisons with post‐processed GIMs further demonstrate that RT‐FAIRS ensures both reliability and responsiveness of the generated real‐time accuracy information. The approach provides a statistically consistent framework for RT‐GIM accuracy information assessment and supports the integrity analysis in real‐time GNSS applications.

Space WeatherVol. 24(4)
Natural Resources Canada (CA), University of Potsdam (DE), Chinese Academy of Sciences (CN), Yangtze Normal University (CN), Qilu Normal University (CN), Federal Agency for Cartography and Geodesy (DE), Aerospace Information Research Institute (CN), GFZ Helmholtz Centre for Geosciences (DE), Qilu Hospital of Shandong University (CN), University of Chinese Academy of Sciences (CN), University of Warmia and Mazury in Olsztyn (PL), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 11%
GNSS positioning and interference
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