SBAS performance improvement with a new undersampled ionosphere threat model based on relative coverage metric

Ionospheric delay error is one of the most significant error sources for single frequency SBAS (Satellite Based Augmentation System) users and its error bound is the key point for PL (protection level) calculation. To satisfy the integrity specifications for users anywhere in the service region, the error bound need to be inflated according to various threat. Among them, the undersampled threat plays an important role in the inflation. The fundamental reason for the undersampled threat lies in the disagreement of the linear planar model to the actual ionosphere characteristics, which cannot be accurately described by the discrete IPP (Ionospheric Pierce Point) samples. Ionosphere threat model is established to handle this problem. It uses historical irregular ionosphere data to generate the two-dimensional lookup table which illustrates the relationship between the IPP distribution and the maximum estimation error. How to abstract the metrics to describe the discrete two-dimensional IPP distribution is the key to the establishment of ionosphere threat model. In this paper, we conclude the properties of a ‘good’ metric from a physical point of view and propose the Relative COVerage (RCOV) metric. Based on the measured data from IGS (International GNSS Service) stations, taking the regions of Europe (20°N~70°N, −30°W~60°E) as an example, the ionosphere threat model based on RCOV metric is established and compared with the RCM (Relative Centroid Metric) model used in WAAS (Wide Area Augmentation System) and MSAS (MTSAT Satellite based Augmentation System). At the same time, the integrity of the ionosphere GIVE (Grid Ionosphere Vertical Error) results is verified. The experimental results show that under the experimental configuration given in this paper, the RCOV metric proposed can improve the system availability on the premise of meeting the integrity requirements.