Simulated Ground Penetrating Radar Data Research Articles

MCA-Based Clutter Reduction From Migrated GPR Data of Shallowly Buried Point Target

Reducing clutter is an important process in terms of improving the detection of targets when using ground penetrating radar (GPR), especially in the case of overlapping target responses and clutter. We present an alternative scheme to remove clutter from monostatic GPR data by combining migration and morphology component analysis (MCA). A simple phase shift migration is first performed on received B-scan data. In the migrated B-scan, clutter, and useful target responses exhibit different morphologies. The clutter appears to be horizontal stripes and the hyperbolic reflection from the target is refocused into an enhanced point-like shape. Subsequently, an overcomplete dictionary is constructed to discriminatively and sparsely represent each morphology based on the simulated GPR data. In particular, the 2-D undecimated discrete wavelet transform is used for the target component, and the 2-D curvelet atoms are used for the clutter. Then, the MCA technique is exploited to sparsely separate the two different components, which leads to the clutter reduction. The sparse representation of 2-D finite-difference-time-domain-based synthetic GPR data illustrates the validity of the overcomplete dictionary. In this paper, the proposed clutter removal method is tested on a synthetic model of point-like targets and real data from buried landmines. The migration concentrates the refracted signals from landmines to their origins, and the shapes of the landmines can be clearly defined. The results of the clutter reduction suggest that the proposed method is more effective than the method implemented directly on the B-scan data and the traditional mean subtraction.

A Hybrid Method Applied to Improve the Efficiency of Full-Waveform Inversion for Pavement Characterization.

Ground penetrating radar (GPR), as a nondestructive testing tool, is suitable for estimating the thickness and permittivity of layers within the pavement. However, it would become problematic when the layer is thin with respect to the probing pulse width, in which case overlapping between the reflected pulses occurs. In order to deal with this problem, a hybrid method based on multilayer perceptrons (MLPs) and a local optimization algorithm is proposed. This method can be divided into two stages. In the first stage, the MLPs roughly estimate the thickness and the permittivity of the GPR signal. In the second stage, these roughly estimated values are used as the initial solution of the full-waveform inversion algorithm. The hybrid method and the conventional global optimization algorithm are respectively used to perform the full-waveform inversion of the simulated GPR data. Under the same inversion precision, the objective function needs to be calculated for 450 times and 30 times for the conventional method and the hybrid method, respectively. The hybrid method is also applied to a measured data, and the thickness estimation error is 1.2 mm. The results show the high efficiency and accuracy of such hybrid method to resolve the problem of estimating the thickness and permittivity of a “thin layer”.

Time-frequency analysis of air-coupled GPR data for identification of delamination between pavement layers

Identification of delamination in pavement layers using ground penetrating radar (GPR) is still challenging due to its limited range resolution. This paper investigates the characteristics of the composite reflection from the air-filled delamination between pavement layers by time-frequency analysis. We firstly simulated GPR data from an asphalt pavement model with an embedded air gap of different thicknesses by the Green’s function method. Then we conducted a laboratory experiment on a delaminated asphalt pavement model. Both the numerical and laboratory experiment results demonstrate that both the peak instantaneous frequency and its amplitude are sensitive to the variation of the air gap thickness. When the thickness of the air gap is smaller than a quarter of the dominant wavelength, the peak instantaneous frequency of the composite reflection is higher than that of the normal interface reflection. We conclude that we can identify the delamination from the overall rise in the peak instantaneous frequency.