The detection of coal/shale interfaces close to the surface using ground penetrating radar (GPR) is difficult because the echo is drowned in unwanted signal components. These components are susceptible to changes in amplitude and cannot be removed well by standard preprocessing techniques. Second order correlation based methods such as matched filtering fail to locate the echo reliably under th...

ENSCO, Inc. is investigating a novel approach to data fusion of magnetic and ground-penetrating radar (GPR) data to characterize previously detected buried targets. The method exploits a single model of the subsurface to predict both magnetic and GPR data observations. By determining the best single model that constrains both data sets, the optimum identification is computed. Using an a priori ...

This chapter discusses the principle and application of two model‐based algorithms for processing non‐dispersive and dispersive ground penetrating radar (GPR) data over layered medium under monostatic antenna configuration. Both algorithms have been selected for their super‐time resolution capability and reduced computational burden; they allow GPR to measure a layer thickness smaller than the ...

Ground Penetrating Radar (GPR) measurements can suffer from large amount of noise and clutter. Current methods, such as time gating and background averaging, mostly applied to remove reflections from air-ground interface do not perform well when removal of extraneous, very strong and non-uniform clutter signals originating from the objects in the surveyed area other than the target is needed. T...

The root growth of trees close to buildings can cause directly or indirectly structural damages and the necessity arises of diagnostic tools to follow their time-spatial behaviour. In this framework, sensing techniques as Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) are of relevant interest since they allow in principle the detection and identification of roots in ...

Fuzzy Clustering is applied to the problem of detecting landmines. Sensor data generated by a Ground Penetrating Radar (GPR) is processed to detect the mines. The GPR produces a three-dimensional array of intensity values, representing a volume below the surface of the ground. Features are computed from this array and clustered using a fuzzy Competitive Agglom-erative (CA) algorithm. Prototypes...

ompressive sensing (CS) is a new method for image sampling in contrast with well-known Nyquist sampling theorem. In addition to the sampling and sparse domain which play an important role in perfect signal recovery on CS framework, the recovery algorithm which has been used also has effects on the reconstructed image. In this paper, the performance of four recovery algorithms are compared accor...

A cooperative target (CT) has been developed to enhance the ground-penetrating radar (GPR) signal-toclutter ratio for buried man-made targets. Applications include tagging high-value buried structures and monitoring microtunnelling equipment. Results are presented for a time-domain CT, comprised of a dipole antenna connected to an unterminated delay line. Multiple GPR measurements made from sep...

Most Ground Penetrating Radar (GPR) measurements are performed on nearly flat areas. If strongly dipping reflections and/or diffractions are present in the GPR data, a classical migration processing step is needed in order to determine the geometries of shallow structures. Nevertheless, a standard migration routine is not suitable for GPR data collected on areas showing a variable and large top...

The landmines presence causes serious safety hazards, which demand the clean up of contaminated land. Ground Penetrating Radar (GPR) is considered as a powerful nondestructive testing tool for high-resolution imaging of the shallow subsurface and its ability to detect both metallic and non-metallic landmines. The contrast in the dielectric constant between a landmine and the surrounding soil is...