A NEW TECHNIQUE BASED ON GREY MODEL FOR FORECASTING OF IONOSPHERIC GPS SIGNAL DELAY USING GAGAN DATA

The ionospheric GPS signal delay which is a function of TEC plays a major role in the estimation positional accuracy of satellite based navigation systems and detrimental to position estimation, especially in strategic applications. Ionospheric TEC is a function of geographical location (Latitude, Longitude), time, season, etc. In this paper, we propose a system theory based Grey Model (GM(1,1)) which uses past and present data for forecasting TEC (GPS signal delay). In this model, data of nine sequential days from five stations of a GPS Aided Geo Augmented Navigation (GAGAN) system network located at different places representing different latitudes, longitudes and equatorial anomaly regions are used to forecast the 10th day TEC values. The performance of the model is assessed by comparing the statistical parameters such as Standard Deviation (SD) and Mean Square Deviation (MSD). The forecasted results are very encouraging. For all the considered five stations, forecasting is better for post sunset time than day time. Also, the results indicate that SD and MSD values are comparatively higher for Trivandrum (near geomagnetic equator) and Ahmedabad (near the crest of the equatorial anomaly region) stations. These results indicate that the proposed model is useful for forecasting of GPS signal delay both for civil aviation and strategic applications.

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