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This thesis aims to answer the question, “What physical process dominates the formation of plasma irregularities, capable of directly or indirectly causing GPS L1 band scintillation, in polar cap plasma patches during magnetic storm conditions?.” A novel modelling technique utilising an ionospheric imaging algorithm is developed and used to elucidate the relative importance of the two most commonly discussed processes. These are the Gradient Drift Instability (GDI) and turbulence induced by electric field mapping to the ionosphere from the magnetosphere. The results show that in magnetic storm conditions, at times the GDI process is dominant, but that at other times turbulence may be as significant as the GDI in determining how the plasma within a polar cap patch behaves, possibly more so. This in turn suggests that further study of the turbulence process is necessary in order to fully understand how big a role it plays in causing GPS L1 band scintillation in the polar cap. The success of the modelling technique developed here shows the utility of ionospheric imaging as a tool for understanding physical problems of the ionosphere; efforts to improve it and to apply it in other contexts would be worthwhile.

The impact the ionospheric electron density has on satellite-based applications, such as satellite communication and navigation systems, is of important consideration, as these signals must propagate through the ionosphere. The excess signal delay due to the ionospheric electron density is one of the main error sources in Global Navigation Satellite Systems (GNSS). One method to study the global behaviour of electron density is ionospheric tomography, a technique that allows estimation of the electron density in the ionosphere through line-integral observations between GNSS satellites and receivers. The research presented in this thesis benefits from the Multi Instrument Data Analysis System (MIDAS) (Mitchell and Spencer, 2003), an ionospheric tomography software that was originally capable of producing global or regional three-dimensional ionospheric electron density reconstructions from GPS observations. GPS-based ionospheric tomography is first assessed in this thesis. This method shows accurate results in regions with high density of ground receivers. However, regions with sparse or uneven ground-receiver coverage give rise to geometric limitations, which lead to large errors in electron density estimation. To overcome this, a multi-GNSS (GPS-GLONASS-Galileo) based ionospheric imaging method is presented in this thesis. The method combines observations from different constellations of satellites orbiting around the Earth, which improves the availability and coverage of measurements for a given receiver network. The technique is evaluated for both under quiet and disturbed geomagnetic conditions, through simulation as well as experiment. The analysis quantifies the improvement of multi-GNSS tomography over single-GNSS tomography for electron density imaging in the ionosphere. The electron density images can be used to apply corrections to ionospheric delay in precise positioning algorithms. Many GNSS precise positioning algorithms rely on ionospheric corrections to calculate the position. However, there is still room for improvement in reducing atmospheric and ionospheric induced errors. Application of corrections from multi-GNSS tomography is therefore proposed in this thesis to support GNSS positioning. Ionospheric corrections from a global network of multi-GNSS receivers are used in a single-frequency positioning method. The results show that this approach allows positioning accuracies comparable to dual-frequency positioning to be obtained, confirming the potential of using ionospheric corrections from multi-GNSS tomography.