Advances in Earth Science ›› 2019, Vol. 34 ›› Issue (1): 103-112. doi: 10.11867/j.issn.1001-8166.2019.01.0103

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Independent Component Extraction and Cross-correlation Spectrum Analysis of Gravity Tide Signal

Dezhao Xing( ),Haiyan Quan *( )   

  1. 1. Kunming University of Science and Technology, Faculty of Information Engineering and Automation, Kunming 650500, China
  • Received:2018-09-13 Revised:2018-12-08 Online:2019-01-10 Published:2019-03-05
  • Contact: Haiyan Quan E-mail:1329459095@qq.com;quanhaiyan@163.com
  • About author:Xing Dezhao (1992-), male, Shenze County, Hebei Province, Master student. Research areas include digital signal processing and geophysical information. E-mail: 1329459095@qq.com |Quan Haiyan (1970-), male, Shiping County, Yunnan Province, Associate professor. Research areas include signal and information processing, intelligent optimization decision-making, geophysical information. E-mail: quanhaiyan@163.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China "Research on key signal processing algorithms for extracting geophysical information and earthquake precursor information from gravity tide signals"(No. 41364002)

Dezhao Xing,Haiyan Quan. Independent Component Extraction and Cross-correlation Spectrum Analysis of Gravity Tide Signal[J]. Advances in Earth Science, 2019, 34(1): 103-112.

The gravity solid tide signal includes daily wave, half-day wave and annual wave and moon wave harmonic component, but the energy of day wave and half-day wave component is relatively strong, and the energy of annual wave and moon wave component is relatively weak. In order to effectively extract these harmonic components with large energy differences and reveal the modulation relationship between them, according to the cause of gravity tide, a gravity solid tide signal decomposition model is used to compare the tidal harmonic components with different strengths. The form of the independent component is decomposed into different orthogonal directions. At the same time, a new optimization algorithm is used to improve the independent component analysis algorithm and separate the independent components of different orthogonal directions. In the spectral correlation analysis of the components of independent components, the autocorrelation operation will make the strong component stronger and the weak component weaker. For this problem, the cross-correlation spectrum between independent components is used to reveal the gravity tide signal., the modulation relationship between harmonic components. The experimental results show that the proposed algorithm not only effectively separates the independent components with large intensity difference in the gravity tide signal from the perspective of additive decomposition, but also reveals the multiplicative modulation relationship between the corresponding tidal harmonics based on the cross-correlation spectrum.

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