地震地质 ›› 2019, Vol. 41 ›› Issue (6): 1511-1528.DOI: 10.3969/j.issn.0253-4967.2019.06.013

• 研究论文 • 上一篇    下一篇

基于SVR模型的电离层TEC背景场构建方法

宋冬梅1,2, 向亮3, 单新建4, 尹京苑5, 王斌1, 崔建勇1   

  1. 1 中国石油大学(华东), 海洋与空间信息学院, 青岛 266580;
    2 青岛海洋科学与技术试点国家实验室, 海洋矿产资源评价与探测技术功能实验室, 青岛 266071;
    3 中国科学院海洋研究所, 青岛 266071;
    4 中国地震局地质研究所, 地震动力学国家重点实验室, 北京 100029;
    5 上海市地震局, 上海 200062
  • 收稿日期:2018-12-05 修回日期:2019-01-18 出版日期:2019-12-20 发布日期:2020-03-10
  • 作者简介:宋冬梅,女,1973年生,教授,主要从事灾害遥感研究,E-mail:songdongmei@upc.edu.com。
  • 基金资助:
    国家自然科学基金(41772350)、上海市科学与技术委员会科研计划项目(16dz1206000)和地震动力学国家重点实验室开放基金(LED2012B02)共同资助

THE METHOD OF CONSTRUCTING IONOSPHERIC TEC BACKGROUND FIELD BASED ON SVR MODEL

SONG Dong-mei1,2, XIANG Liang3, SHAN Xin-jian4, YIN Jing-yuan5, WANG Bin1, CUI Jian-yong1   

  1. 1 College of Ocean and Space Information, China University of Petroleum(East China), Qingdao 266580, China;
    2 The Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China;
    3 Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;
    4 State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China;
    5 Shanghai Earthquake Agency, Shanghai 200062, China
  • Received:2018-12-05 Revised:2019-01-18 Online:2019-12-20 Published:2020-03-10

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

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

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