期刊
JOURNAL OF APPLIED GEOPHYSICS
卷 81, 期 -, 页码 117-121出版社
ELSEVIER
DOI: 10.1016/j.jappgeo.2011.09.004
关键词
GPR; Deconvolution; Signal processing; Kurtosis
Stochastic 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. (C) 2011 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据