RMIT University
Browse

Modeling australian TEC maps using long-term observations of australian regional GPS network by artificial neural network-aided spherical cap harmonic analysis approach

journal contribution
posted on 2024-11-02, 16:44 authored by Wang Li, Dongsheng Zhao, Yi Shen, Kefei ZhangKefei Zhang
The global ionosphere map (GIM) is not capable of serving precise positioning and navigation for single frequency receivers in Australia due to sparse International GNSS Service (IGS) stations located in the vast land. This study proposes an approach to represent Australian total electron content (TEC) using the spherical cap harmonic analysis (SCHA) and artificial neural network (ANN). The new Australian TEC maps are released with an interval of 15 min for longitude and latitude in 0.5◦ × 0.5◦. The validation results show that the Australian Ionospheric Maps (AIMs) well represent the hourly and seasonally ionospheric electrodynamic features over the Australian continent; the accuracy of the AIMs improves remarkably compared to the GIM and the model built only by the SCHA. The residual of the AIM is inversely proportional to the level of solar radiation. During the equinoxes and solstices in a solar minimum year, the residuals are 2.16, 1.57, 1.68, and 1.98 total electron content units (TECUs, 1 TECU = 1016 electron/m2), respectively. Furthermore, the AIM has a strong capability in capturing the adequate electrodynamic evolutions of the traveling ionospheric disturbances under severe geomagnetic storms. The results demonstrate that the ANN-aided SCHA method is an effective approach for mapping and investigating the TEC maps over Australia.

History

Related Materials

  1. 1.
    DOI - Is published in 10.3390/rs12233851
  2. 2.
    ISSN - Is published in 20724292

Journal

Remote Sensing

Volume

12

Number

3851

Issue

23

Start page

1

End page

20

Total pages

20

Publisher

MDPIAG

Place published

Switzerland

Language

English

Copyright

© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Former Identifier

2006105574

Esploro creation date

2022-11-02

Usage metrics

    Scholarly Works

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC