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WANG Shuai, QUAN Lin, WANG Kunpeng, LI Ling, YUAN Gang, KANG Lihua. A Multiplicative Model with Frequency-domain Features Superimposed on Time-domain Mutations for Predicting Ionospheric TEC Methods (in Chinese). Chinese Journal of Space Science, 2025, 45(6): 1439-1450 doi: 10.11728/cjss2025.05.2024-0123
Citation: WANG Shuai, QUAN Lin, WANG Kunpeng, LI Ling, YUAN Gang, KANG Lihua. A Multiplicative Model with Frequency-domain Features Superimposed on Time-domain Mutations for Predicting Ionospheric TEC Methods (in Chinese). Chinese Journal of Space Science, 2025, 45(6): 1439-1450 doi: 10.11728/cjss2025.05.2024-0123
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A Multiplicative Model with Frequency-domain Features Superimposed on Time-domain Mutations for Predicting Ionospheric TEC Methods

doi: 10.11728/cjss2025.05.2024-0123 cstr: 32142.14.cjss.2024-0123
  • 1.

    Beijing Institute of Tracking and Communication Technology, Beijing 100094

  • 2.

    Space Information College, Space Engineering University, Beijing 101416

  • 3.

    School of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan 430074

  • Received Date: 2024-09-30
  • Rev Recd Date: 2025-04-28
    • Available Online: 2025-04-29
    Abstract
  • Total Electronic Content (TEC) is an important characteristic parameter of the ionosphere, which has a great influence on the navigation error correction and other applications, but the current ionospheric TEC prediction accuracy cannot fully meet the demand, and there are deficiencies in the accuracy and lead time. The paper focuses on the needs of regional ionospheric TEC forecasting, comprehensively considers the characteristics of ionospheric TEC in both frequency and time domains, analyzes the ionospheric TEC changes in multiple cycle lengths in the frequency domain according to the characteristics of trend, periodicity, and suddenness of the changes in the ionospheric TEC affected by solar activities, considers the suddenness of the geomagnetic storms and other factors on the ionospheric TEC in the time domain, and considers the Dst index and latitude/longitude as the input parameters for forecasting. Forecast input parameters, and train the specificity of the magnetosphere-ionosphere coupling in each region. The experimental results show that the Root Mean Square Error (RMSE) of the proposed method is better than 1.262 Total Electronic Content Unit (TECU) in the middle latitude region during the geomagnetic lull period. The RMSE of 1-day forecast value is better than 1.094 TECU, and the RMSE of 7-day forecast value is better than 2.771 TECU during high solar activity years. The RMSE of the 7-day forecast value is better than 4.186 TECU and the RMSE of the 1-day forecast value is better than 4.115 TECU during the geomagnetic active period. In this paper, a prediction model with a 7-day lead is established, and the method shows good performance in forecasting accuracy and timeliness.

     

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