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GPR data time varying deconvolution by kurtosis maximization

Vafeidis Antonios, Oikonomou Nikolaos

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URIhttp://purl.tuc.gr/dl/dias/6DB95725-FD52-41B6-8B8E-7550BD99382B-
Identifierhttp://www.sciencedirect.com/science/article/pii/S0926985111001960-
Identifierhttps://doi.org/doi:10.1016/j.jappgeo.2011.09.004-
Languageen-
Extent5 pagesen
TitleGPR data time varying deconvolution by kurtosis maximizationen
CreatorVafeidis Antoniosen
CreatorΒαφειδης Αντωνιοςel
CreatorOikonomou Nikolaosen
CreatorΟικονομου Νικολαοςel
PublisherElsevieren
Content SummaryStochastic and deterministic deconvolution methods encounter difficulties in increasing the temporal resolution of GPR data. Statistical approaches, such as predictive or spiking deconvolution are not effective when the wavelet is not minimum phase, which is the case for GPR data. Wavelet deconvolution is not successful because the shape of the GPR wavelet changes with time. Here, prior to deconvolution, we apply a spectral balancing method in time–frequency (t–f) domain which efficiently produces GPR traces whose dominant frequency does not depend on time. We correct for phase residuals using the maximum kurtosis method. The methodology is demonstrated on synthetic and real GPR data.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-28-
Date of Publication2012-
SubjectGPRen
SubjectDeconvolutionen
SubjectProcessing, Signalen
Subjectsignal processingen
Subjectprocessing signalen
SubjectKurtosisen
Bibliographic CitationN. Economou and A. Vafidis, "GPR data time varying deconvolution by kurtosis maximization", J. Appl. Geoph., vol. 81, pp. 117-121, Jun. 2012. doi:10.1016/j.jappgeo.2011.09.004en

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