Abstract

The ionospheric delay is of paramount importance to radio communication, satellite navigation and positioning. It is necessary to predict high-accuracy ionospheric peak parameters for single frequency receivers. In this study, the state-of-the-art artificial neural network (ANN) technique optimized by the genetic algorithm is used to develop global ionospheric models for predicting foF2 and hmF2. The models are based on long-term multiple measurements including ionospheric peak frequency model (GIPFM) and global ionospheric peak height model (GIPHM). Predictions of the GIPFM and GIPHM are compared with the International Reference Ionosphere (IRI) model in 2009 and 2013 respectively. This comparison shows that the root-mean-square errors (RMSEs) of GIPFM are 0.82 MHz and 0.71 MHz in 2013 and 2009, respectively. This result is about 20%–35% lower than that of IRI. Additionally, the corresponding hmF2 median errors of GIPHM are 20% to 30% smaller than that of IRI. Furthermore, the ANN models present a good capability to capture the global or regional ionospheric spatial-temporal characteristics, e.g., the equatorial ionization anomaly and Weddell Sea anomaly. The study shows that the ANN-based model has a better agreement to reference value than the IRI model, not only along the Greenwich meridian, but also on a global scale. The approach proposed in this study has the potential to be a new three-dimensional electron density model combined with the inclusion of the upcoming Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) data.

Highlights

  • The F2 layer is the most important ionospheric layer, especially during the solar-terrestrial quiet time

  • The results show that this method is very helpful for improving the performances of ionospheric models

  • The “mixed” corrected data (COSMIC and ionosonde) were utilized to develop the ionosphere models for the predictions of frequency of F2 layer (foF2) and hmF2 using an artificial neural network optimized by the genetic algorithm, namely, Global Ionospheric Peak Frequency Model (GIPFM) and global ionospheric peak height model (GIPHM)

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Summary

Introduction

The F2 layer (roughly 150–500 km above the ground) is the most important ionospheric layer, especially during the solar-terrestrial quiet time. This layer is populated by huge numbers of ions and electrons under the dynamic equilibrium condition [1]. The critical frequency of F2 layer (foF2) and its corresponding peak height (hmF2) are the common parameters to represent ionospheric variations. These two parameters play a significant role in the long-distance high-frequency (HF) radio communications since the critical frequency determines the maximum usable frequency according to the electromagnetic theory [2]. With the advancements of space-borne and ground-based instruments and data processed techniques, more attention has been paid to the development and improvement of these ionospheric models [3]

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