Improving the GNSS positioning stochastic model in the presence of ionospheric scintillation

• Published in: Journal of Geodesy
• Main Authors: Aquino, M., Monico, J. F. G., Dodson, A. H., Marques, H., De Franceschi, G., Alfonsi, L., Romano, V., Andreotti, M.
• Other Authors: Universidade Estadual Paulista (UNESP)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer 2009
• Subjects: Global navigation satellites system; Global positioning system; Ionospheric scintillation; Receiver tracking models; Mitigation; Stochastic model; Antarctic; Antarc*
• Online Access: http://hdl.handle.net/11449/6676; https://doi.org/10.1007/s00190-009-0313-6

Engineering and Physical Sciences Research Council (EPSRC) ISACCO Italian Program of Antarctic Researches (PNRA) Ionospheric scintillations are caused by time-varying electron density irregularities in the ionosphere, occurring more often at equatorial and high latitudes. This paper focuses exclusively on experiments undertaken in Europe, at geographic latitudes between similar to 50 degrees N and similar to 80 degrees N, where a network of GPS receivers capable of monitoring Total Electron Content and ionospheric scintillation parameters was deployed. The widely used ionospheric scintillation indices S4 and sigma(phi) represent a practical measure of the intensity of amplitude and phase scintillation affecting GNSS receivers. However, they do not provide sufficient information regarding the actual tracking errors that degrade GNSS receiver performance. Suitable receiver tracking models, sensitive to ionospheric scintillation, allow the computation of the variance of the output error of the receiver PLL (Phase Locked Loop) and DLL (Delay Locked Loop), which expresses the quality of the range measurements used by the receiver to calculate user position. The ability of such models of incorporating phase and amplitude scintillation effects into the variance of these tracking errors underpins our proposed method of applying relative weights to measurements from different satellites. That gives the least squares stochastic model used for position computation a more realistic representation, vis-a-vis the otherwise 'equal weights' model. For pseudorange processing, relative weights were computed, so that a 'scintillation-mitigated' solution could be performed and compared to the (non-mitigated) 'equal weights' solution. An improvement between 17 and 38% in height accuracy was achieved when an epoch by epoch differential solution was computed over baselines ranging from 1 to 750 km. The method was then compared with alternative approaches that can be used to improve the least squares stochastic model such as ...