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Modeling and Prediction of Ionospheric Total Electron Content by Time Series Analysis

机译:时间序列分析法对电离层总电子含量的建模与预测

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摘要

Precise modeling and accurate prediction for the ionospheric total electron content(TEC) are crucial and remain as a challenge for GPS positioning and navigation, space weather forecast, as well as many other Earth Observation System(EOS). This research develops and analyzes a new prediction technique for the regional ionospheric TEC, based on time series analysis theory using autoregressive model (AR) to perform short-term ionospheric TEC prediction. The predicted TEC were then compared with the TEC measured by IGS, and with TEC from the International Reference Ionosphere(IRI) to assess the performance of the model. Preliminary results show that AR model could well describe the variation trend of the regional ionospheric TEC and has a good short-term performance of the ionospheric TEC prediction. The forecasting methodology based on the time series for the regional ionospheric TEC prediction is feasible.
机译:电离层总电子含量(TEC)的精确建模和准确预测至关重要,并且仍然对GPS定位和导航,太空天气预报以及许多其他地球观测系统(EOS)构成挑战。这项研究基于时间序列分析理论,使用自回归模型(AR)进行短期电离层TEC预测,开发并分析了一种新的区域电离层TEC预测技术。然后将预测的TEC与IGS测量的TEC以及国际参考电离层(IRI)的TEC进行比较,以评估模型的性能。初步结果表明,AR模型可以很好地描述区域电离层TEC的变化趋势,并具有良好的短期电离层TEC预测性能。基于时间序列的区域电离层TEC预报方法是可行的。

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