Nonlinear data processing method for the signal enhancement of GPR data

Chih Sung Chen, Yih Jeng

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

An alternative data processing procedure is proposed in this paper for the purpose of enhancing the signal/noise (S/N) ratio of ground penetrating radar (GPR) data. The processing methodology is achieved by performing the logarithmic transform in conjunction with the ensemble empirical mode decomposition (EEMD), a new nonlinear data analysis method in signal processing. The synthetic model study and field example indicate that the logarithmic transform is effective in alleviating the attenuation problem. Additionally, the spectrogram obtained from Hilbert-Huang transform (HHT) shows that the decomposition sensitivity of the EEMD method is greatly improved with the aid of the logarithmic transform. This new method allows us to extract the signal components from noisy GPR data efficiently. The success of this study suggests a possible nonlinear analysis application in future GPR investigation, particularly in the filter design and gain correction.

Original languageEnglish
Pages (from-to)113-123
Number of pages11
JournalJournal of Applied Geophysics
Volume75
Issue number1
DOIs
Publication statusPublished - 2011 Sep 1

Keywords

  • EEMD
  • GPR
  • HHT
  • Logarithmic transform
  • Nonlinear filtering

ASJC Scopus subject areas

  • Geophysics

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