摘要
时间序列分析法是一种重要的统计分析方法,在电离层总电子含量(TEC)短期预测中具有出色的性能,然而,获取TEC数据常面临多重外部干扰和噪声,限制了预测精度的提高。为应对此问题,本文通过融合小波去噪方法与时间序列分析法,提出一种TEC组合预测模型。利用欧洲定轨中心(CODE)发布的2021年高质量数据集,对本文提出的预测模型进行了验证。验证结果显示,该组合模型在高、中、低纬度区域多时段的平均预测精度分别达到95.5726%、91.0294%和86.6899%,相较于传统方法,其在高、中纬度区域的预测性能显著提升,低纬度区域也能够保持稳定状态,有力证明了模型的有效性和可靠性。
Time series analysis is an important statistical analysis method that exhibits excellent performance in short-term predictions of total electron content(TEC)in the ionosphere.However,obtaining TEC data often faces multiple external interferences and noises,which limit the improvement of prediction accuracy.To address this issue,a combined TEC predic⁃tion model was proposed by integrating wavelet denoising methods with time series analysis.The proposed prediction model was validated using a high-quality dataset from the year 2021 released by the Center for Orbit Determination in Europe(CODE).The validation results show that the combined model achieves average prediction accuracies of 95.5726%,91.0294%,and 86.6899%in multiple time periods at high,middle,and low latitude regions,respectively.Compared to traditional methods,it significantly improves prediction performance in high and middle latitude regions and maintains a stable state in low latitude regions,robustly demonstrating its validity and reliability.
作者
王淑娟
WANG Shujuan(Jiangsu Xingyue Surveying and Mapping Technology Company Limited,Yancheng,Jiangsu 224051,China)
出处
《北京测绘》
2025年第9期1318-1324,共7页
Beijing Surveying and Mapping
基金
江苏省自然科学基金(BK20201100)。
关键词
小波去噪
时间序列分析
电离层总电子含量
组合预测模型
wavelet denoising
time series analysis
total electron content in ionosphere
combined prediction model
