朱丹^1,,
刘天佑^1,,,
李宏伟²
1. 中国地质大学(武汉)地球物理与空间信息学院, 武汉 430074
2. 中国地质大学(武汉)数学与物理学院, 武汉 430074

基金项目: 中国地质调查局项目（12120114052001，12120114053101，12120114028001，12120115036201，12120113086100）资助


详细信息

作者简介: 朱丹, 男, 1991年生, 博士研究生, 主要从事位场数据处理及综合解释.E-mail:Zhud_igg@cug.edu.cn

通讯作者: 刘天佑, 男, 1945年生, 教授, 博士生导师, 从事应用地球物理教学和科研.E-mail:liuty@cug.edu.cn

中图分类号: P631

收稿日期:2017-04-20
修回日期:2018-06-07
上线日期:2018-09-05

Separation of potential field based on singular spectrum analysis

ZHU Dan^1,,
LIU TianYou^1,,,
LI HongWei²
1. Institute of Geophysics and Geomatic, China University of Geosciences, Wuhan 430074, China
2. School of Mathematics and Physic, China University of Geosciences, Wuhan 430074, China


More Information

Corresponding author: LIU TianYou,E-mail:liuty@cug.edu.cn

MSC: P631

--> Received Date: 20 April 2017
Revised Date: 07 June 2018
Available Online: 05 September 2018


摘要
摘要:奇异谱分析是一种近年兴起的时间序列分析方法，它利用降秩原理实现信号分离.该方法将数据空间投影到不同特征的子空间中，并用奇异值来表征这些子空间的性质，最后通过截取奇异值实现数据的重构.重磁位场分离可以看成一种多信号叠加的分离问题.不同特征的重磁异常具有不同特征的奇异谱，这是奇异谱分析用于解决位场分离问题的应用基础.本文通过建立理论模型，分析重磁异常的奇异谱特征，得出适用于重磁位场分离的最优参数选择方法，并与传统方法进行比较.对比发现，无论是横向叠加模型、垂向叠加模型还是斜向叠加模型，奇异谱分析都具有很好的分离效果.最后，将奇异谱分析用于鄂东南某矿区的重力资料处理中，实现弱异常的识别和分离.
关键词: 奇异谱分析/
重磁位场分离/
降秩理论/
最优参数/
鄂东南地区

Abstract:Singular spectrum analysis (SSA), which uses the rank reduction to separate signals, is a new method for time series analysis in recent years. In this method, the data space is projected into subspace of different features, which properties are represented by singular values. Then, signal can be reconstructed by hard-thresholding. The potential field separation can be considered as a separation problem of multiple signal superposition. Gravity and magnetic anomalies with different characteristics have different singular spectrum features, which is the application basis of potential field separation. In this paper, synthetic models are established to analyze singular spectrum characteristics of gravity and magnetic anomalies, and we recommend the setting of parameters. Then, we compare SSA with existing methods. It is found that the horizontal superposition model, the vertical superposition model and the diagonal superposition model separated by SSA have the best accuracies. Finally, the singular spectrum analysis is applied to process gravity data to identify and separate the weak anomalies in the mining area of southeastern Hubei.
Key words:Singular spectrum analysis/
Potential field separation/
Rank reduction theory/
Optimal parameter/
Southeastern Hubei



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