Midlatitude Klobuchar correction model based on the k-means clustering of ionospheric daily variations
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The ionosphere influences GNSS radio waves and causes errors in measurements. The majority of GNSS users employ single-frequency receivers that mitigate ionospheric effects by utilizing various models. The GPS system corrects for ionospheric errors through the Klobuchar model, which successfully mitigates approximately 50% of the delay on the global scale; this model estimates the ionospheric delay by using one daily peak value at 14:00 local time (LT) with constant nighttime values. However, the daily ionospheric distribution shows a deviation from the Klobuchar model regarding a secondary peak during periods with higher incoming solar radiation and the occurrence of a nighttime peak. We propose a model, namely the midlatitude Klobuchar correction (ML-KC) model, to correct the Klobuchar model for midlatitude users. The proposed model is a function of the day of the year and the LT of the user adjusted to the local solar time. The dependency on the day of the year is modeled by using the k-means algorithm, thereby producing three clusters based on the correlation between daily modeling coefficients, which are expressed as the ratio between the delay from ionospheric maps and the delay estimated by the Klobuchar model. Furthermore, the time dependency is modeled with three harmonic components. The ML-KC was modeled from ionospheric maps over Europe during the period from 2005 to 2016. The performance of the ML-KC model was tested not only on the same dataset with one additional year of data from 2017 but also in two larger regions different from the modeling area to avoid model overfitting. The performance of the ML-KC model was better than that of the Klobuchar model during all assessed years and areas with the most significant improvements in RMS; during 2011, which demonstrated high solar activity, the RMS improvement reached 36.24%. The proposed model, which can be easily implemented in single-frequency GNSS receivers, offers a simple improvement to the Klobuchar model.
KeywordsIonospheric delay Klobuchar model improvement Midlatitudes k-means clustering GNSS
We would like to express gratitude to the efforts of the International GNSS Service (IGS) for creating and making publicly available scientific data by CDDIS. We are thankful to the NOAA for publishing the continuously operating reference station (CORS) data and to NASA OmniWeb for making the historical solar data available. We would also like to thank all the reviewers on their time and insightful comments which improved our manuscript.
- Brčić D (2015) A model of non-specific daily pattern of the satellite positioning signal ionospheric delay. Ph.D. thesis, Faculty of Maritime Studies, University of Rijeka, Rijeka, CroatiaGoogle Scholar
- CSNO (2018) BeiDou navigation satellite system signal in space interface control document—open service signal B3I (Version 1.0). China Satellite Navigation Office, BeijingGoogle Scholar
- Goswami DY (2015) Principles of solar engineering, 3rd edn. Taylor & Francis Group, Boca Raton, FLGoogle Scholar
- Jongsintawee S, Runraengwajiake S, Supnithi P, Panachart C (2016) Improvement of GPS positioning accuracy when utilizing Klobuchar model with ionospheric conditions in Thailand. In: 2016 13th international conference on electrical engineering/electronics, computer, telecommunications and information technology (ECTI-CON), June 28–July 1, pp 1–5. https://doi.org/10.1109/ecticon.2016.7561391
- Klobuchar JA (1975) A first-order, worldwide, ionospheric, time-delay algorithm. AFCRL-TR-75-0502; air force surveys in geophysics: 324. Ionospheric Physics Laboratory, Air Force Cambridge Research Laboratories, Air Force Systems Command (USAF)Google Scholar
- MacQueen JB (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, Berkeley, 1967, vol 1: statistics. University of California Press, Berkeley, pp 281–297Google Scholar
- Schaer S (1999) Mapping and predicting the Earth’s ionosphere using the global positioning system. Ph.D. dissertation, Astronomical Institute, University of Berne, SwitzerlandGoogle Scholar
- Schaer S, Gurtner W, Feltens J (1998) IONEX: the IONosphere Map EXchange Format Version 1. Astronomical Institute, University of Bern, BernGoogle Scholar
- Stepniak K, Wielgosz P, Paziewski J (2014) Accuracy analysis of the Klobuchar ionosphere model transmitted by the GPS system. In: The 9th international conference “environmental engineering”, selected papers, article number: enviro.2014.246, Vilinus, Lithuania, May 22–23, 2014, pp 1–6. https://doi.org/10.3846/enviro.2014.246