2017
DOI: 10.1093/gji/ggx306
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Improving ambient noise correlation functions with an SVD-based Wiener filter

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Cited by 70 publications
(56 citation statements)
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“…The cross‐correlations were then calculated between each virtual source and all the receivers, resulting in 24 cross‐correlations for each stations pair. To obtain the final NCF, the filter introduced in Moreau, Stehly et al () was applied to each set of cross‐correlations, which were finally stacked. The purpose of this filter is to minimize the incoherent information in the singular vectors of the matrix of pre‐stack correlations with the Wiener filter, for improved convergence of the NCF.…”
Section: Resultsmentioning
confidence: 99%
“…The cross‐correlations were then calculated between each virtual source and all the receivers, resulting in 24 cross‐correlations for each stations pair. To obtain the final NCF, the filter introduced in Moreau, Stehly et al () was applied to each set of cross‐correlations, which were finally stacked. The purpose of this filter is to minimize the incoherent information in the singular vectors of the matrix of pre‐stack correlations with the Wiener filter, for improved convergence of the NCF.…”
Section: Resultsmentioning
confidence: 99%
“…The next step was to filter the correlograms to enhance the signal-to-noise ratio by applying a Singular Value Decomposition-based Wiener filter 71 . The parameters used for this filter were K = 7, L = 7, the filter orders applied to the vertical and horizontal dimensions, respectively, and the number of first singular values was N = 30.…”
Section: Methodsmentioning
confidence: 99%
“…Green's functions are then reconstructed by computing cross correlations for all of the station pairs within each array using the hourly noise data. We apply a two‐dimensional Wiener filter to enhance the signal‐to‐noise ratio, with a filter order of 3 for both vertical (hour) and horizontal (time lag) dimensions (Wang, Tilmann, et al, ; Moreau et al, ) (see the supporting information). For each receiver pair, a reference cross‐correlation function is obtained by stacking cross correlations for that pair over the entire study period.…”
Section: Methodsmentioning
confidence: 99%