Chapter 14: Correlation Using Triaxial Data from Multiple Stations in the Presence of Coherent Noise
M. J. Rutty, S. A. Greenhalgh, 1999. "Correlation Using Triaxial Data from Multiple Stations in the Presence of Coherent Noise", Covariance Analysis for Seismic Signal Processing, R. Lynn Kirlin, William J. Done
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Polarization analysis of single station multicomponent seismic data has been performed with success by several researchers (Montalbetti and Kanasewich, 1970; Vidale, 1986; Flinn, 1965; Esmersoy, 1984; Magotra et al., 1987). The technique has two major objectives: (1) to devise filters to distinguish between events with different modes of vibration (e.g., P- and S-waves versus Rayleigh waves) and (2) to provide a means of estimating the direction of particle motion for use in seismic direction finding.
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Covariance Analysis for Seismic Signal Processing
This reference is intended to give the geophysical signal analyst sufficient material to understand the usefulness of data covariance matrix analysis in the processing of geophysical signals. A background of basic linear algebra, statistics, and fundamental random signal analysis is assumed. This reference is unique in that the data vector covariance matrix is used throughout. Rather than dealing with only one seismic data processing problem and presenting several methods, we will concentrate on only one fundamental methodology—analysis of the sample covariance matrix—and we present many seismic data problems to which the methodology applies.