MODELING PREDICTION OF IONOSPHERIC CHARACTERISTICS NONLINEAR AUTOREGRESSION AND NEURAL NETWORK

Abstract

The terrestrial ionosphere from D-region (60 km) to F-region (500 km) plays an important role in radio wave propagation between the Earth and ionosphere. During the last half-century, a considerable experimental, theoretical, and modeling efforts have been made to understand the physical process occurred in the ionosphere at different altitudes. Radio sensing techniques is widely used to continuously monitor the ionospheric conditions. For example, the ionospheric property in the F2 layer is obtained by a vertical sounding so-called Ionosonde. Properties of the D layer (the lower end of the ionosphere) is effectively obtained by receiving VLF/LF transmitter signals. Although, the ionospheric condition varies both in time and space due to various external forcings from the atmosphere and space weather parameters, quantitative information of contributions influencing the ionosphere from every external forcing have not understood well. In this thesis nonlinear autoregressive with exogenous input and neural network is applied first time to identify the ionospheric characteristics based on the VLF radio wave propagation and ionosonde. One step ahead prediction of the daily nighttime means of VLF electric amplitude in three different latitude paths and two receiving stations by using NARXNN has been carried out. The relative contribution to the ionospheric conditions (VLF electric amplitude variability) from every external forcing has been revealed. Moreover, the proposed model extends for multi-step ahead prediction to evaluate the performance of prediction accuracy for five and ten days ahead. The temporal dependence of F2-region critical frequency (foF2) has been predicted by using the same approach as used for the VLF signals. Physical interpretation of relative contribution to the ionospheric conditions from major external forcing parameters have been made. The results of this thesis can be used to detect anomalies in relation with severe weather, major seismic activity, and space weather to mitigate damages and human victims. Furthermore, we investigate the coupling from external sources between the D- and F-region in the middle-latitude path