Abstract
Abstract. In this paper, Holt-Winters model, ARMA model and ARIMA model in time series analysis were used to predict total electron content (TEC). Taking ionospheric grid data of quiet period and active period in different longitude and latitude provided by IGS center as sample data, the TEC data of the first 8 days were used to build four kinds of prediction models and forecast TEC values of the next 6 days, and the results were compared with the observations provided by IGS center. The prediction effects of the four models in different ionospheric environments and different longitude and latitude are emphatically analyzed. The experimental results showed that the average relative accuracy of ARMA, ARIMA and Holt-Winters models in the quiet and active ionospheric periods for the prediction of 6 days was 89.85% in the quiet period, and 88.76% in the active period. In both periods, the higher the latitude, the lower the RMS value. In addition, VTEC from IGS center value and ARMA model and ARIMA model and Holt - Winters in the quiet period and active forecast VTEC values were compared, in the quiet period or active, four models of forecasting value can better reflect the spatial and temporal variation characteristics of TEC three latitude, the prediction results of the ARIMA model can better reflect the spatial and temporal variation characteristics; But compared with the active period, the prediction results of calm period are relatively good.
Highlights
Distance from the ground, about 60 ~ 1000 km, the atmosphere is called the ionosphere, the radiation from the sun and cosmic rays and various kinds of high-energy charged particles under the action of gas molecules in the region of ionization or completely ionization, and release a lot of free electrons, in the process of satellite signal propagation these free electrons on the navigation and positioning accuracy of the deviation of several meters to tens of meters
Xie et al (2017) use Holt-Winters addition and multiplication model respectively to the International GNSS Service center provide different latitude and longitude ionospheric Total Electron Content (Total Electron Content, total electron content (TEC)) data to carry on the forecast during active and quiet period, the result showed that two kinds of model forecast results are in good agreement with reference, but the additive model can better response change characteristics of the ionosphere TEC
TEC values of the first 8 days were used as sample sequences, and the TEC values of the last 6 days were predicted by Autoregressive Integrated Moving Average Model (ARIMA) model, ARMA model, Holt-Winter addition model and multiplication model, respectively
Summary
Distance from the ground, about 60 ~ 1000 km, the atmosphere is called the ionosphere, the radiation from the sun and cosmic rays and various kinds of high-energy charged particles under the action of gas molecules in the region of ionization or completely ionization, and release a lot of free electrons, in the process of satellite signal propagation these free electrons on the navigation and positioning accuracy of the deviation of several meters to tens of meters. One is the empirical ionosphere model, such as Klobuchar(Klobuchar, 1996), Bent(Bent et al, 1975)and IRI(Patel et al.,2018).The other is to use TEC observation data for short-term prediction, such as neural network model (Chen et al.,2005), spectral analysis(Lu et al.,2014), least-squares configuration (Zhang et al.,2014), and time series (Chen et al.,2011; Tang et al.,2013) model. Sivavaraprasad et al (2017) tested the applicability of the ARIMA, ARMA and Holt-Winter addition and multiplication models to predict ionospheric TEC values under different spatial conditions in low latitudes. In this paper, the global ionospheric map (GIM) provided by the international GNSS (IGS) center will be used to study and analyze the prediction accuracy of ARIMA, ARMA, Holt-Winter addition and multiplication models in different latitudes and ionospheric conditions, in the hope that the study of time series model can promote the development of the prediction of total ionospheric electron content
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