Short-term Prediction and Applicability Analysis of Regional Ionospheric Total Electron Content in Active Period

In the solar active period, the earth's magnetic field is easily affected by the high energy particles of the solar wind, which makes the total electron content of the ionosphere abnormally disturbed, and its non-stationary and nonlinear characteristics are obviously enhanced compared to the calm period. Using the measured data from multiple stations in the 2011 region and the GIM (global ionosphere model) published by the IGS (International GNSS Service) to perform point-by-point modeling, the db4 wavelet basis is used to decompose the sample sequence, and the time series model is used to forecast each component and forecast. Each component is reconstructed so that the ARIMA (auto regressive integrated moving average) model can be improved. The prediction accuracy and applicability of the improved model are evaluated by analyzing the residual ratio of the ARIMA model and the improved model and the distribution of the root mean square error in the experimental region. The results show that the residual error of the improved model and the root mean square error in the experimental area are reduced compared with the ARIMA model, and the improved model can greatly weaken the peak value of the root mean square error in the area.