ABSTRACT

Algorithms that deal with the automatic S-onset time identification problem are a topic of ongoing research. Modern dense seismic networks used for earthquake location, seismic tomography investigations, source studies, early warning, etc., demand accurate automatic S-wave picking. Most of the techniques that have been proposed up to now are mainly based on the polarization features of the seismic waves. We propose a new time domain method for the automatic determination of the S-phase arrival onsets, and present its implementation on local earthquake data. Eigenvalue analysis takes place over small time intervals, and the maximum eigenvalue which is obtained on each step is retained for further processing. In this way, a time series of maximum eigenvalues is formed, which serves as a characteristic function. We obtain a first S-phase arrival time estimation by applying the kurtosis criterion on the derived characteristic function. Furthermore, a multiwindow approach combined with an energy-based weighting scheme is also applied, to reduce the algorithm’s dependence on the moving window’s length and provide a weighted S-phase onset. Automatic picks were compared against manual reference picks, resulting in mean residual time of 0.051 s. Moreover, the proposed technique was subjected to a noise robustness test and sustained a good performance. The mean residual time remained lower than 0.1 s, for noise levels between 1 up to 8 dB. The proposed method is easy to implement, because it is almost parameter free and demands low computational resources.

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