Ionospheric time series forecast based on land-based GNSS
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    Abstract:

    In order to compare the forecast performance of different time series models,the carrier phase smoothing pseudo range method is used to calculate the ionospheric Vertical Total Electron Content (VTEC) over a single station under the condition of calm ionosphere.The Auto Regressive Integrated Moving Average (ARIMA) model and Holt Winters exponential smoothing model are used for station-by-station modeling.A 3-day forecast is achieved through a 9-day sample sequence,and the forecast values are systematically evaluated.The results show that the time series models can well reflect the change in ionospheric VTEC during the forecast period,and the mean square root errors are not more than 5 TECU.In addition,the Holt-Winters multiplicative model has the largest deviation in the forecast value,followed by the additive model.The ARIMA model has higher relative accuracy at the 11 stations than the Holt-Winters exponential smoothing model,and has the smallest root mean square error peak as well as the highest forecast accuracy.

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CHEN Yutian, YUE Dongjie. Ionospheric time series forecast based on land-based GNSS[J]. Journal of Nanjing University of Information Science & Technology,2021,13(2):218-223

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History
  • Received:January 15,2021
  • Online: May 21,2021
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