Inversion of the electric density based on artificial intelligence and VLFsignal propagation during the nighttime and diurnal transition period

A method for the inversion of the electric density in the D-region of the ionosphere based on artificial intelligence and very low frequency (VLF) signal propagation is proposed in this paper. First, how to obtain the solar zenith angle along any VLF wave propagation path is given. Then, the modified electric density profile including linear and Langevin functions is proposed. The parameters of the modified profile versus the solar zenith angle are fitted based on the international reference ionosphere (IRI) model. A model reflecting the relationship between the electric density in the D-region of the ionosphere and VLF wave propagation using the frequency-domain finite element method and artificial intelligence is constructed. The parameters of the modified electric density profile at different solar zenith angles are revised by combining artificial intelligence predicted with observed VLF amplitudes and phases at different universal times during the diurnal transition period. Finally, the diurnal variations of the amplitude and phase of VLF signals from measured data in the reference, the Finite Element Method integrated with the IRI model simulations, and artificial intelligence predictions are compared. This work may provide a new way to invert the electric density in the D-region of the ionosphere and improve the prediction efficiency and accuracy of VLF wave propagation during the nighttime and diurnal transition period.