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Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR
applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal
processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this
research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work
introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is
applied to synthetic and field GPR data acquired over a buried pipe.
The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a
reference signal for pulse compression. For a pulse-compressionfilter, reference signal selection is an important issue, because
as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is
low. Analysis of the results obtained from simulated andfieldGPRdata indicates a significant improvement in theGPRimage,
good discrimination between the target reflection and the ground surface reflection, and better performance with reliable
separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth
of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a
reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.
Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR
applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal
processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this
research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work
introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is
applied to synthetic and field GPR data acquired over a buried pipe.
The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a
reference signal for pulse compression. For a pulse-compressionfilter, reference signal selection is an important issue, because
as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is
low. Analysis of the results obtained from simulated andfieldGPRdata indicates a significant improvement in theGPRimage,
good discrimination between the target reflection and the ground surface reflection, and better performance with reliable
separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth
of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a
reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.
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- Publisher :Korean Society of Earth and Exploration Geophysicists
- Publisher(Ko) :한국지구물리물리탐사학회
- Journal Title :Geophysics and Geophysical Exploration
- Journal Title(Ko) :지구물리와 물리탐사
- Volume : 12
- No :1
- Pages :77~84


Geophysics and Geophysical Exploration






