Global Ionospheric Modeling Using Multi-GNSS and Upcoming LEO Constellations: Two Methods and Comparison

Abstract

Global ionosphere model with high accuracy and resolution is of great importance for ionospheric research and global navigation satellite system (GNSS) precise positioning applications. In the last 20 years, the accuracy and reliability of global ionospheric model benefitted from the development of GNSS technology have been improved significantly, but its performance is still not good over many regions (e.g., oceans and polar region) due to the lack of ground GNSS stations. Fortunately, the rapid development of low earth orbit (LEO) satellite constellations provides a potential opportunity to address this issue. However, there is still no optimal approach to make use of the LEO-based ionospheric observations because of the different observation ranges compared with that of ground-based GNSS ionospheric observations. In this article, two approaches are proposed to combine GNSS and LEO observation data for ionosphere modeling, which are single-layer normalization (SLN) method and dual-layer superposition (DLS) method, respectively. The results exhibit a significant improvement of ionospheric model accuracy by combining LEO and GNSS observation data based on our proposed methods compared with that using GNSS data only, with a reduction in root mean square (rms) error of about 25% and 21% for SLN method and DLS method, respectively. The article also highlights the relations between the performance of ionospheric model estimated by the SLN method and LEO ionospheric observations with different observation accuracy and different satellite cut-off elevations. The results indicate that ionospheric model estimated by GNSS/LEO using SLN method improves at least 25% compared with that by GNSS only. The improvement of ionospheric model estimated with the cut-off elevation of 50° is the best, followed by 70°, and then 20°.