A new global TEC empirical model based on fusing multi-source data

被引:0
|
作者
Jiandi Feng
Ting Zhang
Wang Li
Zhenzhen Zhao
Baomin Han
Kaixin Wang
机构
[1] Shandong University of Technology,School of Civil and Architectural Engineering
[2] State Key Laboratory of Geo-Information Engineering,Faculty of Land Resources Engineering
[3] Kunming University of Science and Technology,undefined
来源
GPS Solutions | 2023年 / 27卷
关键词
Ionosphere; Global TEC empirical model; Multi-source data fusion; Ionospheric anomalies;
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学科分类号
摘要
The global TEC empirical model established with the TEC grid data of IGS as the background has poor prediction accuracy in marine areas, and its ability to describe some ionospheric anomalies is insufficient. In response to the above two problems, we use spherical harmonic (SH) to fuse multi-source TEC data as a modeling dataset and evaluate the accuracy of the fused products. When modeling, we consider three ionospheric anomalies, namely mid-latitude summer nighttime anomaly (MSNA), equatorial ionization anomaly (EIA), and “hysteresis effect,” and establish corresponding model components. We apply the nonlinear least-squares method to establish a global ionospheric TEC empirical model called the TEC model of multi-source fusion (TECM-MF) and verify the model. Results show that: (i) fusion products are valid and reliable modeling data for building global TEC model. (ii) The TECM-MF fits the Fusion TEC input data with a zero bias and a RMS of 3.9 TECU. The model can better show the diurnal, seasonal, and annual variations of the fusion dataset and the “hysteresis effect” of TEC. (iii) In the MSNA area, the prediction ability of the TECM-MF is better, the standard deviation is lower than that of NTCM-GL and Nequick2, close to 1 TECU, and the accuracy is consistent with IRI2016.
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