Validation of a multi-layer approach-based ionospheric mapping function supporting PPP-AR

Abstract One possibility to support Precise Point Positioning with integer Ambiguity Resolution (PPP-AR) is the application of slant ionospheric corrections converted using ionospheric Mapping Functions (MF) from Vertical Total Electron Content (VTEC). In such a case, the accuracy of the ionospheric corrections is driven by the uncertainties introduced by both VTEC and MF. Focusing on the ionospheric mapping functions, we note that a Single Layer Model (SLM) MF, which is conventionally used in GNSS positioning, is less effective for regions with high TEC gradients. Hence, in this study, we validate the performance of a new Multi-Layer (ML) approach-based ionospheric mapping function responding to the limitations of the conventional SLM MF. The new ML MF, based on the Neustrelitz Total Electron Content model, leverages the concept of dividing the ionosphere into several thin shells. Consequently, the ratio of aggregated Slant TEC (STEC) and VTECs provides the mapping factors. We validate the MF based on both PPP positioning and GNSS observation domains. We used data from nine GNSS stations distributed in three ionosphere sectors, namely high, middle, and low latitudes, with different daily patterns of the ionosphere. We report a benefit from applying the new multi-layer approach-based MF for PPP performance compared to positioning with a standard SLM. The advances are the most noticeable during the positioning initialization period and, therefore, are reflected in a faster convergence of the fixed solution by 4–10%, on average. The analysis in the GNSS observation domain based on geometry-free linear combination revealed the highest potential of the ML mapping function for the equatorial region.

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Publication Details

Journal
Satellite Navigation
Published
2026-04-01
DOI
https://doi.org/10.1186/s43020-026-00193-0
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
0.00

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article

Validation of a multi-layer approach-based ionospheric mapping function supporting PPP-AR

Raül Orús Pérez, Grzegorz Nykiel, Paweł Wielgosz, Olaf Frauenberger et al.
Satellite Navigation
GNSS positioning and interference
article

Validation of a multi-layer approach-based ionospheric mapping function supporting PPP-AR

Raül Orús Pérez, Grzegorz Nykiel, Paweł Wielgosz, Olaf Frauenberger, Jacek Paziewski, Narayan Dhital, Rafal Sieradzki, M. Mainul Hoque
article en

Abstract

Abstract One possibility to support Precise Point Positioning with integer Ambiguity Resolution (PPP-AR) is the application of slant ionospheric corrections converted using ionospheric Mapping Functions (MF) from Vertical Total Electron Content (VTEC). In such a case, the accuracy of the ionospheric corrections is driven by the uncertainties introduced by both VTEC and MF. Focusing on the ionospheric mapping functions, we note that a Single Layer Model (SLM) MF, which is conventionally used in GNSS positioning, is less effective for regions with high TEC gradients. Hence, in this study, we validate the performance of a new Multi-Layer (ML) approach-based ionospheric mapping function responding to the limitations of the conventional SLM MF. The new ML MF, based on the Neustrelitz Total Electron Content model, leverages the concept of dividing the ionosphere into several thin shells. Consequently, the ratio of aggregated Slant TEC (STEC) and VTECs provides the mapping factors. We validate the MF based on both PPP positioning and GNSS observation domains. We used data from nine GNSS stations distributed in three ionosphere sectors, namely high, middle, and low latitudes, with different daily patterns of the ionosphere. We report a benefit from applying the new multi-layer approach-based MF for PPP performance compared to positioning with a standard SLM. The advances are the most noticeable during the positioning initialization period and, therefore, are reflected in a faster convergence of the fixed solution by 4–10%, on average. The analysis in the GNSS observation domain based on geometry-free linear combination revealed the highest potential of the ML mapping function for the equatorial region.

Satellite NavigationVol. 7(1)
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Deutsche Gesellschaft für Information und Wissen (DE), European Space Research and Technology Centre (NL), University of Warmia and Mazury in Olsztyn (PL)
European Space Agency, Narodowe Centrum Nauki
Openalex Percentile: Top 24%
GNSS positioning and interference
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