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 language | English |
|---|---|
| Pages (from-to) | 113-123 |
| Number of pages | 11 |
| Journal | Journal of Applied Geophysics |
| Volume | 75 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2011 Sep 1 |
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Keywords
- EEMD
- GPR
- HHT
- Logarithmic transform
- Nonlinear filtering
ASJC Scopus subject areas
- Geophysics
Cite this
Nonlinear data processing method for the signal enhancement of GPR data. / Chen, Chih Sung; Jeng, Yih.
In: Journal of Applied Geophysics, Vol. 75, No. 1, 01.09.2011, p. 113-123.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Nonlinear data processing method for the signal enhancement of GPR data
AU - Chen, Chih Sung
AU - Jeng, Yih
PY - 2011/9/1
Y1 - 2011/9/1
N2 - 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.
AB - 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.
KW - EEMD
KW - GPR
KW - HHT
KW - Logarithmic transform
KW - Nonlinear filtering
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UR - http://www.scopus.com/inward/citedby.url?scp=79961150645&partnerID=8YFLogxK
U2 - 10.1016/j.jappgeo.2011.06.017
DO - 10.1016/j.jappgeo.2011.06.017
M3 - Article
AN - SCOPUS:79961150645
VL - 75
SP - 113
EP - 123
JO - Journal of Applied Geophysics
JF - Journal of Applied Geophysics
SN - 0926-9851
IS - 1
ER -