Receiver Functions from Autoregressive Deconvolution |
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Authors: | Qingju Wu Yonghua Li Ruiqing Zhang Rongsheng Zeng |
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Institution: | (1) Institute of Geophysics, China Earthquake Administration, Beijing, 100081, China |
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Abstract: | Summary Receiver functions can be estimated by minimizing the square errors of Wiener filter in time-domain or spectrum division in
frequency domain. To avoid the direct calculation of auto-correlation and cross-correlation coefficients in Toeplitz equation
or of auto-spectrum and cross-spectrum in spectrum division equation as well as empirically choosing a damping parameter,
autoregressive deconvolution is presented to isolate receiver function from three-component teleseismic P waveforms. The vertical
component of teleseismic P waveform is modeled by an autoregressive model, which can be forward and backward, predicted respectively.
The optimum length of the autoregressive model is determined by the Akaike criterion. By minimizing the square errors of forward
and backward predicting filters, autoregressive filter coefficients can be recursively solved, and receiver function is also
estimated in the similar procedure. Both synthetic and real data tests show that autoregressive deconvolution is an effective
method to isolate receiver function from teleseismic P waveforms in time-domain. |
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Keywords: | Receiver function deconvolution autoregressive model |
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