Implementation of ionospheric prediction algorithm based on huang hilbert transform

Abstract

Global Positioning System (GPS) is primarily a navigation system and most GPS receivers are optimized for navigation application. To reach higher accuracy in air traffic service, India has been developing a satellite based navigation system known as GPS Aided Geo Augmented Navigation (GAGAN). The ionospheric delay is the largest source of error for calculating the accurate position of the receiver using GPS. Total electron content (TEC) and scintillation parameters are derived from GPS measurements which are widely used for ionospheric error studies. These errors can be characterized by the measurement of TEC between GPS receiver and GPS satellites. The TEC data (March 1-10, 2013) collected from the GPS receiver is decomposed using Hilbert-Huang transform (HHT). The HHT is a technique to break down the signal into intrinsic mode functions i.e. IMF's, and acquire instantaneous frequency data. It is designed to work well for data that is non stationary and nonlinear. An Auto Regressive Moving Average (ARMA) model is implemented for forecasting the ionospheric TEC values. In paper, ARMA with HHT algorithm is proposed to forecast the ionospheric variations for providing high precision positional accuracy to GPS users.