Processing Ground Penetrating Radar Data To Improve Resolution Of Near-Surface Targets

Gerlitz, Kevin; Knoll, Michael D.; Cross, Guy; Luzitano, Robert D.; Knight, Rosemary

doi:10.3997/2214-4609-pdb.209.1993_055

Cited by 22 publications

(18 citation statements)

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“…We processed the raw radar data with residual median filtering (Gerlitz et al, 1993) using a window size corresponding to 150 MHz. Then we subtracted the whole radargram median trace from each trace to highlight differences.…”

Section: Field Data and Their Interpretationmentioning

confidence: 99%

Evaluating Ground Penetrating Radar Use for Water Infiltration Monitoring

Saintenoy

Schneider

Tucholka

2008

Vadose Zone Journal

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Ground-Penetrating Radar (GPR) was tested to monitor water infiltration in sand. Water was injected down an 81 cm long tubed hole, with a piezometer recording the depth of water and a tap valve used to adjust it to 15 cm ± 2 cm above the bottom of the tube. During the 20 minutes of infiltration a GPR system recorded a trace every second with its transmitter and receiver antennae at a fixed offset position on the surface. The signal, enhanced by differential correction, allows for tracing the evolution of top and bottom limits of the water bulb in space and time. Comparison with hydrodynamic model of the infiltration process and simulated radargrams prove that the GPR reflections trace the wetting front and the saturation bulb. A quantified estimation of the evolution of the top border of the wetting zone is provided.

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Section: Field Data and Their Interpretationmentioning

confidence: 99%

Evaluating Ground Penetrating Radar Use for Water Infiltration Monitoring

Saintenoy

Schneider

Tucholka

2008

Vadose Zone Journal

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“…In order to obtain satisfactory results, the size of the time window must correspond approximately to the size of the wavelength of the GPR pulse in the media, for the given antenna frequency. If incorrectly applied, severe distortions can be introduced in the amplitude spectrum, or important low-frequency components can remain, in both cases affecting the subsequent processing steps and the final results of the whole processing flow (Gerlitz et al 1993).…”

Section: Figurementioning

confidence: 99%

Enhancing stratigraphic, structural and dissolution features in GPR images of carbonate karst through data processing

Oliveira

Medeiros

Santana

et al. 2019

Near Surface Geophysics

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Obtaining high‐quality ground penetrating radar (GPR) images in karst is difficult because materials resulting from the weathering of carbonate rocks might be electrically conductive. As a consequence, penetration depth and signal resolution might be greatly reduced due to attenuation. In addition, fractures and faults might cause a significant amount of electromagnetic wave scattering. We present a 2D data processing flow which allows improving the quality of GPR images in carbonate karst. The processing flow is composed of the following steps: obtaining a zero‐offset section by removing the direct wave, low‐frequency noise removal, geometrical spreading and exponential gain compensation, spectral balancing, Kirchhoff migration, bandpass filtering, amplitude‐volume enhancement, and topographic correction. For a 200‐MHz dataset, we present in detail each step of the processing flow, exemplifying how to parameterize every step. Spectral balancing is of key importance because it can approximately replenish the high‐frequency content lost due to propagation effects. In this step, we recommend to shift the centroid frequency as much as possible to high‐frequency values, even exceeding the nominal value of the antenna center frequency, but still looking for a band‐limited spectrum as the goal. Despite the difficulty of migrating GPR data, we show that migration (even assuming a constant velocity) might enhance the lateral continuity of the reflection events and allows identification of discontinuities such as faults and fractures. If imaged in a better way, these structures can have special importance as they are often the boundaries of dissolution features. Obtaining images based on amplitude‐volume enhancement techniques allows to better visualize karst voids and deep‐rooted discontinuities because these features are often associated with low‐amplitude zones, which are highlighted in such images. Due to this processing flow, stratigraphic, structural and dissolution features can be enhanced, allowing the interpreter to establish spatial and genetic associations among these elements to obtain a better understanding of the karst formation process.

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“…4(b) map to the narrow region around p = 0 ns/m. From the τ-p sections, only the data in a small rectangular window (Table 1) with τ-values larger than 20 ns, con- amount of wavy reflections (Cagnoli and Ulrych 2001) or to separate air and ground waves from reflections caused by nearsurface interfaces (Gerlitz et al 1993). Kim et al (2007) applied it to the attenuation of ringing noise in vertical GPR profiles.…”

Section: Linear Radon Transformmentioning

confidence: 99%

2D and 3D ground‐penetrating radar surveys with a modular system: data processing strategies and results from archaeological field tests

Verdonck

Vermeulen

Docter

et al. 2013

Near Surface Geophysics

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Recently, the use of ground-penetrating radar (GPR) arrays with a large number of antenna elements in a fixed configuration has become more common. The investment needed for these systems is significant. In order to reduce the recording time in the field, an alternative is the use of several single GPR antennas in parallel (a ‘modular system’). Although this does not match the fast acquisition of detailed data sets by means of multi-channel arrays, a system consisting in single antennas can gradually be expanded and investment can be spread over time. This paper presents a 2D and a full-resolution 3D survey, conducted with a modular GPR instrument. A characteristic of these systems is that the cross-line separation between transmitter-receiver pairs is larger than the sampling distance prescribed by the Nyquist theorem. As a consequence, for 3D data collection, profiles have to be acquired between previously recorded ones, which requires high positioning accuracy. A completely identical response for different single GPR antennas is difficult to achieve. For the system tested, on less favourable soils this resulted in striping in the horizontal slices. Several methods (3D frequency-wavenumber filtering, eigenimage filtering, mean profile filtering and filtering based on discrete wavelet transform, discrete ridgelet transform and linear Radon transform) were applied to two data sets exhibiting different kinds of linear noise and their capability to suppress artefacts was assessed. Although overall a reduction of the stripe patterns was achieved, mostly it was impossible to fully eliminate the noise in the time-slices without low-pass filtering in the cross-line direction. For the 2D data, low-pass filtering caused loss of some of the archaeological response and therefore was not applied. Mean profile filtering allowed the most reliable characterization of the archaeological structures

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Processing Ground Penetrating Radar Data To Improve Resolution Of Near-Surface Targets

Cited by 22 publications

References 0 publications

Evaluating Ground Penetrating Radar Use for Water Infiltration Monitoring

Evaluating Ground Penetrating Radar Use for Water Infiltration Monitoring

Enhancing stratigraphic, structural and dissolution features in GPR images of carbonate karst through data processing

2D and 3D ground‐penetrating radar surveys with a modular system: data processing strategies and results from archaeological field tests

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