Abstract-Local Area Augmentation System (LAAS) is expected to enable the pilots to guide the aircraft more precisely and safely into busy airports even in poor visibility conditions. The anomalous low and equatorial latitude Ionosphere is severe threat to the LAAS system. To characterize the anomalous ionospheric gradients, the performance of an ionospheric threat model is evaluated. In our investigation, in contrast to the reported work available in the open literature, smoothed code phase measurements are used in the threat model to obtain precise ionospheric time delay. The three key parameters of the threat model gradient slope (mm/km), width (km) and front speed (m/s) are used in the analysis. Further, geometry screening using Maximum Ionosphere Induced Error in Vertical (MIEV) as a key parameter is carried out to identify the stationary gradients and its impact on system performance for CAT-I operations. A maximum ionospheric gradient of 355.74 mm/km over a distance of approximately 75 km is reported at mid latitudes. Whereas, in our findings at low/equatorial latitudes even within a distance of approximately 4 km a maximum gradient of 460 mm/km is observed, which is comparatively very high. Our results show that, there is necessity to enhance upper bound for the ionospheric gradients threat space over low latitudes.

The positional accuracy of Indian Global Positioning System Aided Geo Augmented Navigation (GAGAN) system is affected by many errors and among them the ionospheric time delay error is the predominant error. The Indian ionosphere is characterised by large gradients, intense irregularities and equatorial anomaly conditions and hence suitable ionospheric model is necessary for GAGAN. Compared with global and regional ionospheric models, not much significant work is reported on local ionospheric models for Indian region. In this study, using Indian Satellite Based Augmentation System data, a local ionospheric model based on Taylor series expansion (TSE) is used. Initially, a network of 17 GAGAN total electron content stations data are considered in the analysis for both quiet and disturbed days. The ionospheric time delay results of the TSE model indicate that the model is performing better for quiet days than the disturbed days. The delay because of the TSE model is compared with that of the delays because of Klobuchar and IRI-2007 models and experimental GAGAN data. The obtained results shows that the TSE model is estimating delay more closely with respect to GAGAN data than that of the Klobuchar and IRI-2007 models and may be considered for use in offline applications.

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