Abstract: There are many factors related to the variations of TEC, and the changes of TEC caused by earthquake only occupy a small portion. Therefore, it is vital how to exclude the ionospheric interference of non-seismic factors accurately in the process of seismic ionospheric anomaly extraction. This study constructed a TEC non-seismic dynamic background field considering the influence of solar and geomagnetic activities. Firstly, the TEC components of half-year cycle and annual cycle are extracted by wavelet decomposition. Then, it establishes a regression model between TEC in which periodic factors are removed and solar activity index, geomagnetic activity index with SVR method(support vector regression)in non-seismic period. Finally, based on the constructed model, the solar activity index and geomagnetic activity index is used to reconstruct aperiodic components of TEC in earthquake's period. From the reconstructed aperiodic components of TEC plus the half-year periodic components and annual periodic components of TEC in the same period, the non-seismic dynamic background field is obtained. Comparing the residuals relative to original TEC values in non-seismic dynamic background field and traditional sliding window background, there are apparent monthly periodic change and semi-annual periodic change in the residuals of sliding window background, which can have obvious impacts on the subsequent seismic ionospheric anomaly detection. In order to test the validity of seismic TEC anomaly detection based on the background field construction method, this paper investigated the long time series TEC anomalies near Wenchuan city(30°N, 100°E)from March 1 to September 26 in 2008. It is found that under the condition of non-seismic disturbance such as solar activity and geomagnetic activity, TEC abnormal disturbance is rarely detected by non-seismic dynamic background field method, when compared with the traditional sliding time-window method. And before the earthquake, more TEC anomalies were detected based on the proposed method, also, they were more intense than those extracted by sliding window method. Therefore, the TEC background field construction method based on SVR(support vector regression)has superiorities in both system errors elimination, which are caused by solar, geomagnetism, the non-seismic ionospheric disturbance events and periodic fluctuations of TEC, and in reducing the false alarm rate of seismic TEC anomaly. Moreover, it can also improve the seismic TEC anomaly detection ability. In addition, this paper analyzed the time-spatial distribution of TEC anomaly before three earthquakes on May 12, August 21 and August 30, 2008. They were mainly negative abnormal perturbations and often distributed on the equatorial side of epicenter.

Key words: ionosphere, TEC(Total Electron Content), SVR(Support Vector Regression), wavelet analysis, Wenchuan earthquake

摘要： 引起电离层电子浓度总含量（Total Election Content，TEC）变化的因素有很多，而地震TEC扰动只是很小的一部分。文中尝试构建一个考虑了太阳活动与地磁活动影响的TEC非震动态背景场，对比分析TEC非震动态背景场和传统的滑动时窗背景相对于原始TEC值的残差情况，滑动时窗背景的残差存在明显的月周期与半年周期，该周期性残差将对后续的地震电离层异常探测造成重要影响。同时，利用非震动态背景场法与滑动时窗法探测了汶川附近研究点（30°N，100°E）2008年3月1日—9月26日长时间序列的TEC异常情况，发现在太阳活动、地磁活动等非震干扰的情况下，相较于传统的滑动时窗法，TEC非震动态背景场法很少检测出TEC异常扰动；而在地震发生前，基于文中的方法提取的TEC异常较滑动时窗法提取的异常强度更大、异常次数更多。最后，文中分析了汶川地区2008年5月12日、8月21日、8月30日3次地震前的TEC异常表现，均主要为负异常扰动，且异常主要分布在震中靠近赤道一侧。

关键词: 电离层, 电离层电子总量, SVR模型, 小波分析, 汶川地震