Multi-GNSS Algorithms for Real-Time VTEC and DCB Estimation

Abstract

Understanding the total electron content of the ionosphere is crucial for several reasons, foremost to increase the accuracy of GNSS signals by eliminating ionosphere-caused delays but also to understand space weather for example. This thesis shows how to determine the total electron content in the ionosphere by forming three different approaches: code-phase levelled single station processing, phase-only single station processing, and network processing. By using these approaches, time-varying STEC estimates per satellite are converted into time-varying VTEC estimates per station by means of a mapping function. This conversion is obtained by using an ionospheric model. In this thesis, two different mapping functions are compared with each other: single layer model (SLM) and modified single layer model (MSLM). The results show that due to the conceptual similarities between them, the solutions are correlated. Furthermore, the SLM mapping function is investigated via using different shell heights to investigate an optimal shell height over the globe. However, the results indicated that there is no unique shell height representing the globe ideally. This is due to the complex dynamics of the ionosphere and because the single layer approximation is not sufficient to model the ionosphere. In order to enhance the estimations, ionospheric gradients up to the 2nd order are considered. The result show significant improvements by including 1st order gradients, however, including 2nd order gradients does not result in any significant improvements. The code-phase levelled single station processing, the phase-only single station processing, and the network processing solutions are compared with the IGS solutions. The results indicate that the network processing solutions provide the best fit with respect to official IGS solutions.