|Abstract:||Global Navigation Satellite Systems (GNSS) underpin a number of modern life activities, such as air/marine transport, autonomous vehicles/machinery control and in areas such as construction, agriculture and offshore operations. GNSS signals are sensitive to a number of vulnerabilities, of which a one major shortcoming is related to the perturbations due to the Earth’s ionosphere. In particular, a phenomenon known as ionospheric scintillation, characterised by rapid fluctuations in GNSS signal amplitude and phase, may seriously disrupt satellite tracking and degrade system accuracy, reliability and integrity. The research presented in this paper was carried out under the “Ionosphere Prediction Service” (IPS) project funded by the European Commission (EC) under Horizon 2020, in the frame of the Galileo programme. The main aim of this project is to translate the forecast of the ionosphere into GNSS userdevoted metrics through the design and development of a prototype for an ionospheric prediction service. The statistical models developed to estimate the 3D positioning errors at the high and low latitudes as a function of scintillation levels are presented. The statistical approach of non-linear regression was applied on a long-term data set to develop these models. If scintillation information can be nowcasted, the developed statistical models can be used to nowcast the 3D positioning errors on a regional or a global scale, which can provide GNSS users with the expected error in the 3D position estimation under scintillation.|
Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)
September 24 - 28, 2018
Hyatt Regency Miami
|Pages:||3827 - 3832|
|Cite this article:||
Veettil, S. Vadakke, Aquino, M., De Franceschi, G., Spogli, L., Cesaroni, C., Romano, V., "Statistical Models to provide Meaningful Information to GNSS End-users Under Ionospheric Scintillation Conditions," Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 3827-3832.
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