Eigenimage-Based Signal Processing for Subsurface Inhomogeneous Clutter Reduction in Ground-Penetrating Radar Images

Title
Eigenimage-Based Signal Processing for Subsurface Inhomogeneous Clutter Reduction in Ground-Penetrating Radar Images
Authors
현승엽김세윤
Keywords
eigen-image; Subsurface Inhomogenity; ground-penetrating radar; Eigenimage Filtering; clutter reduction
Issue Date
2012-11
Publisher
한국전자파학회논문지; The Journal of Korea Electromagnetic Engineering Society
Citation
VOL 23, NO 11, 1307-1314
Abstract
To reduce the effects of clutters with subsurface inhomogenities in ground-penetrating radar(GPR) images, an eigenimage based signal-processing technique is presented. If the conventional eigenimage filtering technique is applied to B-scan images of a GPR suvey, relatively homogeneous clutters such as antenna ringing, direct coupling between transmitting and receiving antennas, and soil-surface reflection, can be removed sufficiently. However, since random clutters of subsurface inhomogenities still remain in the images, target signals are distorted and obscured by the clutters. According to a comparison of the eigenimage filtering results, there is different coherency between subsurface clutters and target signals. To reinforce the pixels with high coherency and reduce the pixels with low coherency, the pixel-by-pixel geometric-mean process after the eigenimage filtering is proposed here. For the validity of the proposed approach, GPR survey for detection of a metal target in a randomly inhomogeneous soil is numerically simulated by using a random media generation technique and the finite-difference time-domain(FDTD) method. And the proposed signal processing is applied to the B-scan data of the GPR suvey. We show that the proposed approach provides sufficient enhancement of target signals as well as remarkable reduction of subsuface inhomogeneous clutters in comparison with the conventional eigenimage filtering.
URI
http://pubs.kist.re.kr/handle/201004/44353
ISSN
12263133
Appears in Collections:
KIST Publication > Article
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