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State Space Approach to Signal Extraction Problems in Seismology

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Time Series Analysis and Applications to Geophysical Systems

Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 139))

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Abstract

State space methods for extracting signal from noisy seismic data are shown. The method is based on the general state space model, recursive filtering and smoothing algorithms. The self-organizing state space model is used for the estimation of time-varying parameter of the model. In this paper, we show five specific examples of time series modeling for signal extraction problems related to seismology. Namely, we consider 1) the estimation of the arrival time of a seismic signal, 2) the extraction of small seismic signal from noisy data, 3) the detection of the coseismic effect in groundwater level data contaminated by various effects from air pressure etc., 4) the estimation of changing spectral characteristic of seismic record, and 5) spatial-temporal smoothing of OBS data.

This is an expository article based on the previous papers [22], [24], [25]. A part of this study was carried out under the ISM Cooperative Research Program (2001-ISM-CRP-2026).

The work of the first author was supported in part by Grant-in-Aid for Scientific Research (B)(2) 13558025 and (C)(2) 12680321 from Japan Society for the Promotion of Science.

Concerning Section 7, he is grateful to the coauthors of the paper [25].

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Author information

Authors and Affiliations

  1. The Institute of Statistical Mathematics, Minato-ku, Tokyo, 106-8569, Japan

    Genshiro Kitagawa

  2. Institute of Seismology and Volcanology, Hokkaido University, Sapporo, 060-0810, Japan

    Tetsuo Takanami

  3. Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology, Tsukuba, 305-8567, Japan

    Norio Matsumoto

Authors
  1. Genshiro Kitagawa
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  2. Tetsuo Takanami
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  3. Norio Matsumoto
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Editor information

Editors and Affiliations

  1. Department of Statistics, University of California, Berkeley, 367 Evens Hall, Berkeley, CA, 94720-3860, USA

    David R. Brillinger

  2. Department of Earth and Environmental Engineering Henry Krumb School of Mines, Columbia University, 918 Seeley Mudd Building, 500 120th Street, New York, NY, 10027, USA

    Enders Anthony Robinson

  3. Department of Statistics, University of California, Los Angeles, 8142 Math-Science Building, Los Angeles, CA, 90095-1554, USA

    Frederic Paik Schoenberg

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Kitagawa, G., Takanami, T., Matsumoto, N. (2004). State Space Approach to Signal Extraction Problems in Seismology. In: Brillinger, D.R., Robinson, E.A., Schoenberg, F.P. (eds) Time Series Analysis and Applications to Geophysical Systems. The IMA Volumes in Mathematics and its Applications, vol 139. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-9386-3_2

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  • DOI: https://doi.org/10.1007/978-1-4684-9386-3_2

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-1971-7

  • Online ISBN: 978-1-4684-9386-3

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