Abstract
State space method for the extraction of small seismic signal from noisy observation is shown in this article. In the basic model, it is assumed that the observed time series is consisted of the three components, namely the background noise, seismic signal and the observation noise components. Autoregressive models are used for the background noise component and the seismic signal component and they are estimated from the observed time series by the maximum likelihood method. The observation noise is assumed to be a white noise sequence. In this state space method, the estimation of the time-varying innovation variance of the seismic signal model is crucial. In this article, two methods based on the piecewise modeling and the self-organizing state space modeling are shown. To illustrate the method, the results of the analysis of the foreshock of Urakawa-Oki earthquake were shown.
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© 2003 Springer-Verlag
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Kitagawa, G., Takanami, T. (2003). Extraction of small seismic signal by state space modeling. In: Methods and Applications of Signal Processing in Seismic Network Operations. Lecture Notes in Earth Sciences, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0117694
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DOI: https://doi.org/10.1007/BFb0117694
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