摘要
为揭示电离层不同频段电磁信号的结构差异及其特征表现，针对多频信号分量可比性不足的问题，本文使用STL对CSES观测的ULF、ELF、VLF及HF频段电场数据进行统一分解。在固定观测区域与时间窗口下，对各频段信号的趋势项、周期项与残差项进行分析与对比。结果表明，STL能够在不同频段有效分离趋势与周期成分，残差主要反映短时扰动及非平稳信息；ULF与ELF频段趋势平缓、周期稳定，VLF频段以趋势成分为主导，HF频段趋势与周期特征相对较弱。研究结果揭示了STL方法在多频电场信号分析中的适用性与差异性，为基于残差项开展震前异常检测提供了方法基础。
关键词： 电离层扰动；STL；多频段分析；残差项；趋势与周期
Abstract
To reveal the structural differences and characteristic manifestations of ionospheric electromagnetic signals across different frequency bands, and to address the issue of insufficient comparability among multi-frequency signal components, this paper employs Seasonal-Trend decomposition using Loess to perform a unified decomposition of electric field data observed by the China Seismo-Electromagnetic Satellite in the ULF, ELF, VLF, and HF bands. Under a fixed observation area and time window, the trend, seasonal, and residual components of the signals in each frequency band are analyzed and compared. The results indicate that STL can effectively separate the trend and seasonal components across different frequency bands, with the residual component mainly reflecting short-term disturbances and non-stationary information. Specifically, the ULF and ELF bands exhibit smooth trends and stable seasonalities; the VLF band is dominated by the trend component; and the HF band shows relatively weak trend and seasonal characteristics. These findings reveal the applicability and variability of the STL method in analyzing multi-frequency electric field signals, providing a methodological basis for pre-earthquake anomaly detection based on residual components.
Key words： Ionospheric disturbance; STL; Multi-frequency analysis; Residual component; Trend and periodic
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