Abstract
Abstract
Ionospheric delay is one of the dominant error sources affecting the positioning accuracy of global navigation satellite systems (GNSS), and single-frequency users in particular rely on ionospheric models for delay mitigation. Empirical models such as IRI-Plas 2020 are widely used in ionospheric studies, but their global accuracy and practical positioning performance still require systematic assessment. Using GNSS-derived VTEC from 124 globally distributed stations in 2021, representing low solar activity, and 2024, representing high solar activity, this study evaluates IRI-Plas 2020 under two configurations, with and without assimilation of Global Ionospheric Map (GIM) TEC, and further investigates its correction performance in standard single point positioning (SPP). The results show that GIM TEC assimilation substantially improves the VTEC accuracy of IRI-Plas 2020. The mean RMSE is reduced from 4.999 TECU to 1.827 TECU in 2021 and from 7.847 TECU to 2.369 TECU in 2024, corresponding to reductions of approximately 63% and 70%, respectively. The GIM-assimilated configuration also maintains relatively small mean biases of 1.117 TECU and 0.669 TECU in 2021 and 2024, respectively, whereas the non-assimilated configuration shows larger systematic deviations and stronger error dispersion, especially under high-solar-activity conditions. In the SPP experiments based on selected quiet and disturbed 30-day windows in 2024, the GIM-assimilated IRI-Plas configuration consistently outperforms the Klobuchar model and the non-assimilated IRI-Plas configuration. Relative to Klobuchar, it reduces the mean 3D positioning RMSE by approximately 34%–41% during the quiet window and 28%–49% during the disturbed window, depending on latitude band. These results demonstrate that GIM TEC assimilation can effectively improve both the global VTEC accuracy and the single-frequency positioning applicability of IRI-Plas 2020, while retaining its profile-consistent ionosphere–plasmasphere modeling capability.
Direct answer
What can I do from this paper page?
Use this page to scan "Global accuracy and positioning performance of the IRI-Plas 2020 ionospheric model based on GNSS TEC" quickly: start with the summary and abstract, then check the authors, source, topics, and related papers. From here, open Scollr to follow GNSS positioning and interference research, save the paper, or map adjacent work.
Research areas
Follow related topics
Citation
BibTeX
@article{Li2026Global,
title = {Global accuracy and positioning performance of the IRI-Plas 2020 ionospheric model based on GNSS TEC},
author = {Li Li and X F Wang and Zhao Li and Ying Liu},
journal = {Discover Applied Sciences},
year = {2026},
doi = {10.1007/s42452-026-09108-9},
url = {https://doi.org/10.1007/s42452-026-09108-9}
}
FAQ
Using this paper in a discovery workflow
How do I find related work for this paper?
Use the related papers and topic links on this page as starting points. In Scollr, you can also open the paper and build a literature map around its references, citing papers, and related work.
How can I keep up with new GNSS positioning and interference research papers?
Follow GNSS positioning and interference research in Scollr. New papers from the topic flow into a personalized feed, and you can save useful studies to revisit later.
Can I cite this paper from this page?
This page includes a static BibTeX block for Global accuracy and positioning performance of the IRI-Plas 2020 ionospheric model based on GNSS TEC. Always verify the DOI, source, and publication details against the publisher record before submitting a manuscript.
Follow this research in Scollr
Follow the topics and authors behind this paper, save useful studies, and build a literature map when you are ready to go deeper.
Get the app