Nikos Economou

Spectral balancing GPR data using time-variant bandwidth in the t-f domain

Ground-penetrating radar (GPR) sections encounter a resolution reduction with depth because, for electromagnetic (EM) waves propagating in the subsurface, attenuation is typically more pronounced at higher frequencies. To correct for these effects, we have applied a spectral balancing technique, using the S-transform (ST). This signal-processing technique avoids the drawbacks of inverse Q* filtering techniques, namely, the need for estimation of the attenuation factor Q* from the GPR section and instability caused by scattering effects that result from methods of dominant frequency-dependent estimation of Q* . The method designs and applies a gain in the time-frequency ( t-f ) domain and involves the selection of a time-variant bandwidth to reduce high-frequency noise. This method requires a reference amplitude spectrum for spectral shaping. It performs spectral balancing, which works efficiently for GPR data when it is applied in very narrow time windows. Furthermore, we have found that spectral balancin...

Time-varying deconvolution of GPR data in civil engineering

Ground Penetrating Radar (GPR) profiles are often used in civil engineering problems. Overlapping reflections from thin subgrade layers are observed when a relatively low frequency antenna is used. An efficient GPR data processing method, which increases the dominant frequency of GPR data and the temporal resolution, is proposed. It is implemented in the t–f domain. The proposed time-varying deconvolution technique avoids the need for both the calculation of an inverse zero-phase whitening operator and subsequently the application of a band-pass filtering. The user must select the dominant frequency of the Ricker wavelet and use the phase of a reference electromagnetic wavelet, which is acquired experimentally, for stationary dephasing. Apart from delineating thin layers, this method reduces the number of antennas for imaging both shallow and deeper layers in civil engineering. The effectiveness of the proposed method is demonstrated through four civil engineering applications.

Deterministic deconvolution for GPR data in the t-f domain

Deconvolution methods encounter difficulties in increasing the temporal resolution of GPR data due mainly to non-stationarity of the records. GPR wavelets are typically mixed phase, which is additionally a major failure of standard deconvolution methods. Here, we propose a deterministic deconvolution method for GPR data, implemented in the t-f domain, which utilizes narrow time windows and sets spectral balancing as a precondition. A reference wavelet is estimated experimentally for the calculation of a time varying deconvolution operator. Its phase variation is extracted from the spectrally balanced deconvolved GPR trace. The algorithm, tested on synthetic and real data, produces very promising results. In particular the deconvolved GPR section acquired over sands exhibits better temporal resolution and reveals reflected waves travelling through high loss media.

Contribution of electrical tomography methods in geotechnical investigations at Mavropigi lignite open pit mine, Northern Greece

In this paper, the application of 2D and 3D electrical resistivity methods in geotechnical investigations is explored through a case study in Northern Greece. These two methods were employed at a lignite surface mining operation where fracture zones and discontinuities have been recently observed close to the pit boundaries. The main aim of the geophysical survey was to estimate the inclination of the contact between the Neogene and Schist/Carbonate formations near the southern limits of the pit, as well as to estimate the thickness of the carbonate rocks on top of the Schist formations to evaluate the stability of the southern slopes. Synthetic data were initially generated to help plan an efficient electrical tomography survey, in a region with complex geology and irregular terrain. Three configurations (Wenner–Schlumberger and dipole–dipole or pole–dipole) proved essential in such conditions and helped improving the resolution of the resistivity section. The sections were then calibrated by boreholes. Finally, the geophysical survey provided invaluable data regarding the geometry of the bedrock and possible faults, which was essential for the slope stability calculations.

Time-varying band-pass filtering GPR data by self-inverse filtering

Even though ground penetrating radar data signal processing has already been studied by many researchers, more research is needed and expected from automatic ground penetrating radar data analysis. An automatic band-pass filtering procedure can lead to sufficient real-time data interpretation as signal buried in noise could be amplified. Ground penetrating radar traces are highly nonstationary, requiring time-varying processing techniques. An algorithm, based on self-inverse filtering, which is a special case of inverse filtering, was implemented. It is a ground penetrating radar trace filtering approach and is implemented by applying inverse filtering in each time sample in the time-frequency domain. Applied on a synthetic trace, this algorithm performed better than a stationary band-pass filter and empirical mode decomposition family methods, whereas its application on real ground penetrating radar data from two different sites enhanced reflections buried in noise without the need to test different high-frequency band stops and with minimum distortion of the signal and the initial temporal resolution of the data.

GPR Data Processing Techniques

Ground penetrating radar (GPR) is a non-destructive geophysical method that uses radar pulses to image the subsurface. Notwithstanding that it is particularly promising for soil studies, GPR is characterised by notoriously difficult automated data analysis. Hence, the focus of this chapter is to provide the reader with a deep understanding of the state of the art and open issues in the field of GPR data processing techniques as well as of the interesting application of GPR in the field of civil engineering. In particular, we present an overview on noise suppression, deconvolution, migration, attribute analysis and classification techniques for GPR data.

GPR data time varying deconvolution by kurtosis maximization

Stochastic and deterministic deconvolution methods encounter difficulties in increasing the temporal resolution of GPR data. Statistical approaches, such as predictive or spiking deconvolution are not effective when the wavelet is non-minimum phase, which is the case for GPR data. Wavelet deconvolution is not successful due to the non-stationarity of the GPR trace. Here, prior deconvolution, we apply a spectral balancing method in t-f domain which efficiently reduces the non-stationarity. The proposed methodology involves correction for phase residuals using the maximum kurtosis method. The effectiveness of this methodology is demonstrated on synthetic and real GPR data.

Application of Classification Methods on Geophysical Data from the Archaeological Site of Aptera, Chania, Greece

Classification techniques such as the self-organizing-maps (SOM) network are proposed as a tool for efficient interpretation of geophysical data obtained from archaeological investigation. This methodology was useful for the interpretation of georadar data from the archaeological site of Aptera, Chania, Greece where an integrated geophysical survey covered 9730 m2. The survey was realized under the auspices of the 25th Ephorate of Prehistoric and Classical Antiquities, Ministry of Culture. Soil resistance and magnetic gradient maps, resistivity and georadar sections and 3D images, aerial and ground photos, archaeological and geologic maps were registered in a GIS project. The geophysical maps display the ancient city plan. Resistivity depth slices exhibit a stone corridor at a depth of 0.34 m. Three-dimensional inversion was applied on electrical tomography data collected along parallel survey lines. The resulted three-dimensional image reveals a water pipeline. Instantaneous and geometric attributes calculated from the migrated georadar sections over a roman cistern were subsequently classified using SOM. The resulted classified 3D georadar image displays the arc-shaped roof of the cistern as well as stone pipelines which supplied the cistern with rain water.

Time Varying Zero-phase Filtering of GPR Data for Imaging Pavement Layers

GPR profiles are often used in imaging the pavement layers. Overlapping reflections from thin subgrade layers are observed when a relatively low frequency antenna is used. An efficient method for road monitoring, which increases the dominant frequency of GPR data and the temporal resolution, is proposed. It is implemented in the t-f domain. The proposed zero-phase filtering technique is equivalent to zero-phase deconvolution. It avoids the need for both the calculation of an inverse zero-phase whitening operator and subsequently the application of a band pass filtering. The user must select the dominant frequency of the Ricker wavelet. Apart from delineating thin layers, this method reduces the number of antennas for imaging both shallow and deeper layers in road monitoring.

Advanced Ground Penetrating Radar Signal Processing Techniques

Ground penetrating radar (GPR) is a non-destructive geophysical method that uses electromagnetic waves to image the subsurface. A typical GPR system has three main components: transmitter and receiver, directly connected to the transmitting and receiving antennas, and a control unit. Electromagnetic pulses are transmitted into the subsurface and the earth response is recorded. The GPR method is characterized by the rapidly decaying amplitude of the electromagnetic waves, together with the loss of the relevant higher frequency harmonics. Thus, GPR data are highly non-stationary and processing is inherently a challenge. GPR technology has seen tremendous progress in its range of applications, as well as in the analysis and processing algorithms, over the past 20 years. GPR applications currently include sedimentology, ground-water contamination, glaciology, archaeology and cultural-heritage management, civil and geotechnical engineering, planetary exploration, demining, and more. Even though there is an undoubted promise for this technique regarding the most of the above-mentioned applications, the most successful results have come from glaciology, archaeology and civil engineering. GPR signal processing and subsequent display/presentation of the results are of paramount importance to GPR operators and end-users. They should be considered as an integrated part of the methodology, as well as a prerequisite for successful surveying and data interpretation. In April 2013, the COST (European COoperation in Science and Technology) Action TU1208 “Civil Engineering Applications of Ground Penetrating Radar” officially started. This Action focuses on the exchange of scientific-technical knowledge and experience of GPR techniques in civil engineering. It has established several new active links between universities, research institutes, companies and end users working in the field, fostering and accelerating its long-term development in Europe. It is also having a strong impact in promoting throughout Europe a wider and more effective use of this safe and non-destructive inspection method. The Action is now in progress and the leading Guest Editors of this Special Issues are coordinating the scientific activities of Project 3.4, focused on the development of advanced GPR data-processing algorithms. Such Project is part of Working Group 3 of the Action, which is dealing with the improvement and implementation of accurate and fast electromagnetic-scattering methods for the characterization of GPR scenarios, imaging and inversion techniques, and effective data-processing algorithms for the elaboration of GPR data collected during civil-