Ionospheric Modelling using GPS to Calibrate the MWA. II: Regional ionospheric modelling using GPS and GLONASS to estimate ionospheric gradients

TL;DR

This paper advances regional ionospheric modelling by integrating GPS and GLONASS data from multiple stations near MRO, improving gradient estimation and exploring variable-height models, though denser GNSS networks are needed for small-scale features.

Contribution

It introduces a multi-station approach combining GPS and GLONASS data, enhancing ionospheric gradient modelling over previous single-station methods.

Findings

Improved data quality via cycle slip detection and repair.

Inclusion of GLONASS data enhances model accuracy.

Small-scale ionospheric features require denser GNSS networks.

Abstract

We estimate spatial gradients in the ionosphere using the Global Positioning System (GPS) and GLONASS (Russian global navigation system) observations, utilising data from multiple GPS stations in the vicinity of Murchison Radio-astronomy Observatory (MRO). In previous work the ionosphere was characterised using a single-station to model the ionosphere as a single layer of fixed height and this was compared with ionospheric data derived from radio astronomy observations obtained from the Murchison Widefield Array (MWA). Having made improvements to our data quality (via cycle slip detection and repair) and incorporating data from the GLONASS system, we now present a multi-station approach. These two developments significantly improve our modelling of the ionosphere. We also explore the effects of a variable-height model. We conclude that modelling the small-scale features in the ionosphere that have been observed with the MWA will require a much denser network of Global Navigation Satellite System (GNSS) stations than is currently available at the MRO.