Time series analysis model based on electromagnetic detection data

Due to the demand for the time matching of different satellites data during cross-calibration of electromagnetic detection data, this paper analyzes the error distribution features of electron density (N_e) simulated based on the international reference ionosphere (IRI) model at different latitudes by using the time series data of DEMETER satellite. At the same time, based on the autoregre-ssive integrated moving average (ARIMA) model, the N_e data time series forecasting model is constructed. By comparing with the IRI model, the advantages and disadvantages of ARIMA model are analyzed in simulated prediction of the N_e time series data. The results show that the relative error of ARIMA forecasting model is small in the short-time (the relative error less than 10%), however, becomes greater in the long time. Whereas, the relative error of IRI model in simulated prediction of N_e time series data does not become larger in the long time, and the relative error at high latitudes is lower than that at low and moderate latitudes.