The Applicability of Neural Networks to Ionospheric Modeling in Support of Relocatable Over-The-Horizon Radar

Ionospheric models have been developed to interpret Relocatable Over- the-Horizon Radar data. This thesis examines the applicability of neural networks to ionospheric modeling in support of Relocatable Over-the-Horizon Radar. Two neural networks were used for this investigation. The first network was trained and tested on experimental ionospheric sounding data. Results showed neural networks are excellent at modeling ionospheric data for a given day. The second network was trained on ionospheric models and tested on experimental data. Results showed neural networks are able to learn many ionospheric models and the modeling network generally agreed with the experimental data. Ionosphere research, Ionospheric forecasting, Ionospheric radio wave propagation, Neural networks, Over-the-horizon radar.