Auto Regressive Ionospheric Prediction model for GPS Applications

Global Positioning System (GPS) is a satellite based navigation system. The GPS system positional accuracy is limited by ionospheric error. Ionospheric delay is a function of Total Electron Content (TEC). Prediction of ionospheric delays is very important for high precision application such as civil aircraft landing and missile guidance application. In this paper, a new modeling technique known as an Auto Regressive (AR) model is proposed for predicting the TEC values. This model is based on short term time series analysis. This model works with basic principle of regression, where past data i. e. Previous days TEC is used for predicting future values. The GPS data by Hyderabad station are considered. It is found that the AR model gives better results for short term predictions.