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<p>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.</p>

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Global accuracy and positioning performance of the IRI-Plas 2020 ionospheric model based on GNSS TEC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月16日

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  • Lei Li,
  • Xiaoman Wang,
  • Zhao Li,
  • Yi Liu

摘要

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.