Methodology for the characterisation of the impact of TEC fluctuations and scintillation on ground positioning quality over South America and North Europe, with implications for forecasts

A variety of economic sectors rely upon the use of Global Navigation Satellite Systems (GNSS) in areas such as autonomous navigation, timing, land management, oil exploration, precision agriculture, civil aviation. Spatial and temporal gradients (or irregularities) in the ionospheric plasma density distribution introduce disturbances on the propagation of GNSS radio signals. These propagation disturbances originate additional errors and outages that degrade the positioning quality, thus producing an impact on GNSS-based applications. The quantification of the impact that ionospheric disturbances can have on GNSS users is important because mitigation strategies can be implemented accordingly. Although the morphology of ionospheric disturbances is well understood, the prediction of their impact on GNSS applications still represents a challenge: in this respect, traditional maps of ionospheric indices do not provide helpful information to users and services regarding the impact. The main limitation is due to the difficulty in accurately describing and forecasting the spatial and temporal variability of ionospheric irregularities and their likely impact on the quality of ground positioning and navigation. Here, a novel method was developed for the characterisation of the spatial and temporal variability of the propagation disturbances associated with the presence of ionospheric irregularities and how this relates to the impact on ground positioning likely to be experienced by users over a given region and a given temporal interval. The method is based on the combination of the concept of sky maps (describing the occurrence of ionospheric disturbances by means of joint probabilities) and the concept of ground maps (describing the impact on the ground positioning quality by means of the 3-D positioning error, the time dilution of precision, and the occurrence of data gaps). The method can be utilised in near real time or in conjunction with a prediction model. The method facilitates the exploration of the relationship between the spatial and temporal variability of ionospheric propagation disturbances, and the quality of ground positioning, thus informing on the impact on ground positioning quality likely to be experienced over a given area.