UDC 528.4
CSCSTI 36.23
Global navigation satellite systems (GNSS) are significantly affected by ionospheric delays, which impact on the accuracy of coordinate determination. In this study, the performance of three ionospheric correction models was evaluated: Klobuchar, NeQuick-G, and IRI-2016 – in various geographic regions, including the territory of the Russian Federation. The research is based on data from the first day of each month in 2023, using vertical total electron content (VTEC) values calculated at regular grid points with a 2.5° latitude and 5.0° longitude step. The accuracy of these models is assessed using the root mean square (RMS) of the difference in VTEC calculated by the models and global ionospheric maps (GIM). The analysis covers the entire Earth’s surface, polar regions, mid-latitude regions, equatorial regions, and the territory of the Russian Federation. The Klobuchar model demonstrates the lowest accuracy, particularly in polar regions, where its accuracy values do not exceed 45 % and lower than that of the other models. In equatorial regions, its accuracy is only 9 % lower. The NeQuick-G and IRI-2016 models show similar overall accuracy, but NeQuick-G provides more accurate results in specific cases, with RMS values as low as 2 TECU, while IRI-2016 offers more predictable results with RMS values not exceeding 8–10 TECU. For the territory of the Russian Federation, the NeQuick-G model is most effective during calm ionospheric periods, with an RMS of 4.702 TECU, and the IRI-2016 model is preferred during disturbed conditions, with an RMS of 5.335 TECU.
GNSS, GNSS receiver, ionospheric models, ionospheric measurement correction, Klobuchar model, NeQuick-G, IRI, total electron content
1. Antonovich K.M. Ispol'zovanie sputnikovyh radionavigacionnyh sistem v geodezii: monografiya: v 2 t. M.: Kartgeocentr, 2005. T. 1. 334 s.
2. Yasyukevich Y., Zatolokin D., Yasyukevich A., et al. Ionosphere Models Validation: TEC and Positioning Domain // AGU Fall Meeting Abstracts. New Orleans LA, 2021. P. SA44B-09.
3. Nibigira J. de D., Ratnam D.V., Sivakrishna K. Performance Analysis of NeQuick-G, IRI-2016, IRI-Plas 2017 and AfriTEC Models over the African Region during the Geomagnetic Storm of March 2015 // Geomagnetism and Aeronomy. 2023. Vol. 63. P. 83–98. DOIhttps://doi.org/10.1134/s0016793223600601.
4. Yasyukevich Y.V., Zatolokin D., Padokhin A., et al. Klobuchar, NeQuickG, BDGIM, GLONASS, IRI-2016, IRI-2012, IRI-Plas, NeQuick2, and GEMTEC Ionospheric Models: A Comparison in Total Electron Content and Positioning Domains // Sensors. 2023. Vol. 23. No. 10. P. 4773. DOIhttps://doi.org/10.3390/s23104773.
5. Tian Y., Li S., Shen H., et al. Comparative analysis of BDGIM, NeQuick-G, and Klobuchar ionospheric broadcast models // Astrophysics and Space Science. 2022. Vol. 367. No. 8. P. 78. DOIhttps://doi.org/10.1007/s10509-022-04109-7.
6. Gatica-Acevedo V.J., Sergeeva M.A., Maltseva O.A., et al. TEC variations and IRI-2016, IRI-2020 and IRI-Plas performance in Mexico // Advances in Space Research. 2025. Vol. 75. No. 5. P. 4260–4273. DOIhttps://doi.org/10.1016/j.asr.2024.03.046.
7. Liu J., Jia X., Zhu Y., et al. Comparing GNSS TEC data from the African continent with IRI-2016, IRI-Plas, and NeQuick predictions // Advances in Space Research. 2022. Vol. 69. No. 7. P. 2852–2864. DOIhttps://doi.org/10.1016/j.asr.2022.01.008.
8. Atıcı R., Sağır S., Emelyanov L.Y., et al. Investigation of ionospheric electron density change during two partial solar eclipses and its comparison with predictions of NeQuick 2 and IRI-2016 Models // Wireless Personal Communications. 2021. Vol. 118. P. 2239–2251. DOIhttps://doi.org/10.1007/s11277-021-08122-x.
9. Aragon-Angel A., Zürn M., Rovira-Garcia A. Galileo ionospheric correction algorithm: An optimization study of NeQuick-G // Radio Science. 2019. Vol. 54. No. 11. P. 1156–1169. DOIhttps://doi.org/10.1029/2019RS006875.
10. Montenbruck O., González Rodríguez B. NeQuick-G performance assessment for space applications // GPS Solutions. 2020. Vol. 24. P. 13. DOIhttps://doi.org/10.1007/s10291-019-0931-2.
11. Bilitza D., Altadill D., Truhlik V., et al. International Reference Ionosphere 2016: From ionospheric climate to real-time weather predictions // Space Weather. 2017. No. 15. P. 418–429. DOIhttps://doi.org/10.1002/2016SW001593.
12. Yuan Y., Wang N., Li Z., et al. The BeiDou global broadcast ionospheric delay correction model (BDGIM) and its preliminary performance evaluation results // Navigation. 2019. Vol. 66. No. 1. P. 55–69. DOIhttps://doi.org/10.1002/navi.292.
13. Zhu Y., Tan S., Zhang Q., et al. Accuracy evaluation of the latest BDGIM for BDS-3 satellites // Advances in Space Research. 2019. Vol. 64. No. 6. P. 1217–1224. DOIhttps://doi.org/10.1016/j.asr.2019.06.021.
14. Ivanov V.B., Gorbachev O.A., Kholmogorov A.A., et al. Optimization and testing of the GEMTEC model of total electron content in the ionosphere // Cosmic Research. 2015. Vol. 53. P. 267–271. DOIhttps://doi.org/10.1134/S0010952515040036.
