Space Weather Forecasting for Satellite-based Positioning Systems
Satellite-based navigation- and positioning systems (GNSS, like GPS, Galileo) are continuously exposed to disturbances from the atmosphere. The phenomenon, which is caused by density variations in electrically charged particles in the atmosphere, is called Space Weather. Because there is no relief from Space Weather, it is vital to develop a forecasting service. This thesis presents the need for a Space Weather forecast by analysing the performance of a commercially available GNSS based positioning system, CPOS. Next, a method to predict the worst disturbances on GNSS systems is presented. A mathematical model of the polar cap atmosphere is used to calculate how the particle density will develop, and thus when and where the disturbances will occur. We combine the model with observations from ground receivers, radars and satellite data. We verify the model using observations from Svalbard, and find that the model can predict the time of the worst disruptions with an accuracy of 5 minutes. Lastly, we present a method to monitor the atmospheric density using the Swarm satellites, which could serve as input to the forecast algorithm without relying on ground based observations.