A Bayesian Approach to Improve Regional and Global Ionospheric Maps using GNSS Observations
- 1Department of Surveying and Geomatics Engineering, University of Tehran, Iran
- 2Robert Bosch GmbH, Abstatt, Germany
- 3School of Earth and Ocean Sciences, Cardiff University, Wales, UK
The Global Ionosphere Maps (GIMs) are generated on a daily basis at the Center for Orbit Determination in Europe (CODE) using the observations from about 200 Global Positioning System (GPS)/GLONASS sites of the International GNSS Service (IGS) and other institutions. These maps contain Vertical Total Electron Content (VTEC) values, which are estimated in a solar-geomagnetic reference frame using a spherical harmonics expansion up to degree and order 15. Although these maps have wide applications, their relatively low spatial resolution limits the accuracy of many geodetic applications such as those related to Precise Point Positioning (PPP) and navigation. In this study, a novel Bayesian approach is proposed to improve the spatial resolution of VTEC estimations in regional and global scales. The proposed technique utilises GIMs as a prior information and updates the VTEC estimates using a new set of base-functions (with better resolution than that of spherical harmonics) and the GNSS measurements that are not included in the network of GIMs. To achieve the highest accuracy possible, our implementation is based on a transformation of spherical harmonics to the Slepian base-functions, where the latter is a set of bandlimited functions that reflect the majority of signal energy inside an arbitrarily defined region, yet they remain orthogonal within this region. The new GNSS measurements are considered in a Bayesian update estimation to modify those of GIMs. Numerical application of this study is demonstrated using the ground-based GPS data over South America. The results are also validated against the VTEC estimations derived from independent GPS stations.
Key words: Spherical Slepian Base-Functions, Spherical Harmonics, Ionospheric modelling, Vertical Total Electron Content (VTEC)
How to cite: Farzaneh, S. and Forootan, E.: A Bayesian Approach to Improve Regional and Global Ionospheric Maps using GNSS Observations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-282, https://doi.org/10.5194/egusphere-egu2020-282, 2019