Evaluation of the regional ionosphere using final, ultra-rapid, and rapid ionosphere products
-
Ramadan Kamel
,
Nour Bassim Frahat
Abstract
The ionosphere plays a critical role in radio wave propagation, impacting satellite-based communication and navigation systems. This study evaluates near-real-time ionosphere maps (NRTIMs) derived from dual-frequency Global Positioning System (GPS) observations and validates them against established ionosphere models. Using dual-frequency Global Navigation Satellite System (GNSS) technology, the research mitigates ionospheric errors by measuring phase delays at L1 and L2 frequencies. Global ionosphere maps (GIMs) generated by the International GNSS Service (IGS) provide essential ionospheric corrections. Our approach combines accurate GPS observations with regional modeling to enhance GNSS positioning accuracy. The results demonstrate the effectiveness of the developed MATLAB algorithm in estimating ionospheric delays, showing strong convergence with GIMs. The results show a significant convergence between the Regional Ionosphere Modeling of RIM, IGS (Final Ionosphere Product), IGU (Ultra Rapid Ionosphere Product), and IGR (Rapid Ionosphere Product), as the highest average values during the 77th DOY of winter 2020 at the CPVG station were 14.753 TECU for RIM and 14.736, 14.7373 and 14.731 TECU at the CPVG station for IGS, IGU, and IGR while the average was for RIM, IGS, IGU, and IGR are respectively lower, with the lowest average values during the 190th DOY of autumn 2020 at station IZMI with a value of 3.5472 TECU for RIM, 3.5541, 3.5421 and 3.5624 TECU at IZMI station for IGS, IGU, and IGR respectively. By achieving strong agreement with existing GIMs and providing high-frequency results, the algorithm improves the reliability of GPS systems by effectively monitoring envelope disturbances. Ionic and dilute.
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state there is no conflict of interest.
-
Research funding: None declared
-
Data availability: Not applicable.
References
1. Sedeek, A. Validation of regional and global ionosphere maps from GNSS measurements versus IRI2016 during different magnetic activity. J Appl Geodesy 2022;16:229–40. https://doi.org/10.1515/jag-2021-0046.Search in Google Scholar
2. Sherif, A, Rabah, M, Mousa, A, Zaki, A, Anwar, M, Sedeek, A. Ionospheric TEC modeling using COSMIC-2 GNSS radio occultation and artificial neural networks over Egypt. J Appl Geodesy 2024;18:359–74. https://doi.org/10.1515/jag-2023-0079.Search in Google Scholar
3. Elsayed, A, Sedeek, A, Dome, M, Rabah, M. Vertical ionospheric delay estimation for single-receiver operation. J Appl Geodesy 2019;13:81–91. https://doi.org/10.1515/jag-2018-0041.Search in Google Scholar
4. Klobuchar, JA. Ionospheric time-delay algorithm for single-frequency GPS users. IEEE Trans Aero Electron Syst 1987:325–31. https://doi.org/10.1109/taes.1987.310829.Search in Google Scholar
5. Prieto-Cerdeira, R, Orús-Pérez, R, Breeuwer, E, Lucas-Rodriguez, R, Falcone, M. Performance of the Galileo single-frequency ionospheric correction during in-orbit validation. GPS World 2014;25:53–8.Search in Google Scholar
6. Yuan, Y, Wang, N, Li, Z, Huo, X. The BeiDou global broadcast ionospheric delay correction model (BDGIM) and its preliminary performance evaluation results. Navigation 2019;66:55–69. https://doi.org/10.1002/navi.292.Search in Google Scholar
7. Wageeh, A, Doma, M, Sedeek, A, Elghazouly, A. DCB estimation and analysis using the single receiver GPS/GLONASS observations under various seasons and geomagnetic activities. Adv Space Res 2023;72:3933–45. https://doi.org/10.1016/j.asr.2023.07.063.Search in Google Scholar
8. Sherif, A, Rabah, M, Mousa, A, Zaki, A, Sedeek, A. Assessing the performance of IRI-2016 and IRI-2020 models using COSMIC-2 GNSS radio occultation TEC data under different magnetic activities over Egypt. J Appl Geodesy 2024;18:163–76. https://doi.org/10.1515/jag-2023-0068.Search in Google Scholar
9. Yuan, YB, Tscherning, CC, Knudsen, P, Xu, G, Ou, JK. The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS. J Geodesy 2008;82:1–8. https://doi.org/10.1007/s00190-007-0152-2.Search in Google Scholar
10. Mannucci, AJ, Wilson, BD, Yuan, DN, Ho, CM, Lindqwister, UJ, Runge, TF. A global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci 1998;33:565–82. https://doi.org/10.1029/97rs02707.Search in Google Scholar
11. Roma-Dollase, D, Hernández-Pajares, M, Krankowski, A, Kotulak, K, Ghoddousi-Fard, R, Yuan, Y, et al.. Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle. J Geodesy 2018;92:691–706. https://doi.org/10.1007/s00190-017-1088-9.Search in Google Scholar
12. Wanninger, L, Beer, S. Rapid and accurate ionospheric delay corrections for single-frequency GPS users. J Geodesy 2006;80:298–307.Search in Google Scholar
13. Schaer, S. Mapping and predicting the earth’s ionosphere using the global positioning system [Ph.D. thesis]. Bern: University of Bern; 1999.Search in Google Scholar
14. Hernández-Pajares, M, Juan, JM, Sanz, J, Orús, R. The use of the ionospheric pierce point concept in GNSS positioning: a review. J Geodesy 2009;83:953–65.Search in Google Scholar
15. Tawfeek, H, Sedeek, A, Rabah, M, El-Fiky, G. Regional ionosphere mapping using zero difference GPS carrier phase. Ann Geophys Discuss 2018. https://doi.org/10.5194/angeo-2018-121.Search in Google Scholar
16. Leandro, RF. Precise point positioning with GPS: a new approach for positioning, atmospheric studies, and signal analysis [Ph.D. dissertation]. Fredericton, New Brunswick, Canada: Department of geodesy and Geomatics Engineering, University of New Brunswick; 2009:232 p., Technical Report No. 267.Search in Google Scholar
17. Sedeek, AA, Doma, MI, Rabah, M, Hamama, MA. Determination of zero difference GPS differential code biases for satellites and prominent receiver types. Arabian J Geosci 2017;10:58. https://doi.org/10.1007/s12517-017-2835-1.Search in Google Scholar
18. Jin, R, Jin, S, Feng, G. M_DCB: MATLAB code for estimating GPS satellite and receiver differential code biases. GPS Solut 2012;16:541–8. https://doi.org/10.1007/s10291-012-0279-3.Search in Google Scholar
19. Kao, S, Tu, Y, Chen, W, Weng, D, Ji, S. Factors affecting the estimation of GPS receiver instrumental biases. Surv Rev 2013;45:59–67. https://doi.org/10.1179/1752270612Y.0000000022.Search in Google Scholar
20. Zhao, X, Jin, S, Mekik, C, Feng, J. Evaluation of regional ionospheric grid model over China from dense GPS observations. Geodesy Geodyn 2016;7:361e368. https://doi.org/10.1016/j.geog.2016.04.011.Search in Google Scholar
21. Rocken, C, Kuo, YH, Schreiner, W, Hunt, D, Sokolovskiy, S, McCormick, C. COSMIC system description. Terr Atmos Ocean Sci 2000;11:21–52. https://doi.org/10.3319/TAO.2000.11.1.21(COSMIC.Search in Google Scholar
22. Rui, T, Qin, Z, Guanwen, H, Hong, Z. On ionosphere-delay processing methods for single-frequency precise-point positioning. J Geodesy Geodyn 2011;2:71–6. https://doi.org/10.3724/SP.J.1246.2011.00071.Search in Google Scholar
23. Sedeek, A. Low-cost positioning performance using remotely sensed ionosphere. Egypt J Remote Sens Space Sci 2021;24:945–60. https://doi.org/10.1016/j.ejrs.2021.07.004.Search in Google Scholar
24. Available from: https://igs.org/products.Search in Google Scholar
© 2024 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Special Issue: Joint International Symposium on Deformation Monitoring 2025
- Impact of mathematical correlations
- Employing variance component estimation for point cloud based geometric surface representation by B-splines
- Deterministic uncertainty for terrestrial laser scanning observations based on intervals
- Investigating the potential of stochastic relationships to model deformations
- Laser scanning based deformation analysis of a wooden dome under load
- Classifying surface displacements in mining regions using differential terrain models and InSAR coherence
- Water multipath effect in Terrestrial Radar Interferometry (TRI) in open-pit mine monitoring
- Multi-temporal GNSS, RTS, and InSAR for very slow-moving landslide displacement analysis
- Reviews
- Evaluation of the regional ionosphere using final, ultra-rapid, and rapid ionosphere products
- Experiences with techniques and sensors for smartphone positioning
- Original Research Articles
- Crustal deformation estimation using InSAR, West of the Gulf of Suez, Egypt
- Factors affecting the fitting of a global geopotential model to local geodetic datasets over local areas in Egypt using multiple linear regression approach
- Utilization of low-cost GNSS RTK receiver for accurate GIS mapping in urban environment
- Seasonal variations of permanent stations in close vicinity to tectonic plate boundaries
- Time-frequency and power-law noise analyzes of three GBAS solutions of a single GNSS station
- A 2D velocity field computation using multi-dimensional InSAR: a case study of the Abu-Dabbab area in Egypt
Articles in the same Issue
- Frontmatter
- Special Issue: Joint International Symposium on Deformation Monitoring 2025
- Impact of mathematical correlations
- Employing variance component estimation for point cloud based geometric surface representation by B-splines
- Deterministic uncertainty for terrestrial laser scanning observations based on intervals
- Investigating the potential of stochastic relationships to model deformations
- Laser scanning based deformation analysis of a wooden dome under load
- Classifying surface displacements in mining regions using differential terrain models and InSAR coherence
- Water multipath effect in Terrestrial Radar Interferometry (TRI) in open-pit mine monitoring
- Multi-temporal GNSS, RTS, and InSAR for very slow-moving landslide displacement analysis
- Reviews
- Evaluation of the regional ionosphere using final, ultra-rapid, and rapid ionosphere products
- Experiences with techniques and sensors for smartphone positioning
- Original Research Articles
- Crustal deformation estimation using InSAR, West of the Gulf of Suez, Egypt
- Factors affecting the fitting of a global geopotential model to local geodetic datasets over local areas in Egypt using multiple linear regression approach
- Utilization of low-cost GNSS RTK receiver for accurate GIS mapping in urban environment
- Seasonal variations of permanent stations in close vicinity to tectonic plate boundaries
- Time-frequency and power-law noise analyzes of three GBAS solutions of a single GNSS station
- A 2D velocity field computation using multi-dimensional InSAR: a case study of the Abu-Dabbab area in Egypt
