Sparse Reconstruction From GPR Data With Applications to Rebar Detection

Soldovieri, Francesco; Solimene, Raffaele; Monte, Lorenzo Lo; Bavusi, M.; Loperte, A.

doi:10.1109/tim.2010.2078310

Cited by 82 publications

(37 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 has several drawbacks. First of all, the retrieved contrast function depends on the electrical properties of the background (Soldovieri et al, 2011). Moreover, due to the Born approximation, the reconstructions are only qualitative; i.e., they provide an indication about the position and approximate shape of the targets (Leone and Soldovieri, 2003;Persico et al, 2005).…”

Section: Coupling Of Thermal and Electromagnetic Methodsmentioning

confidence: 99%

A joint thermal and electromagnetic diagnostics approach for the inspection of thick walls

Touz

Dumoulin

Gennarelli

et al. 2017

Geosci. Instrum. Method. Data Syst.

Self Cite

View full text Add to dashboard Cite

Abstract. In this study, we present an inversion approach to detect and localize inclusions in thick walls under natural solicitations. The approach is based on a preliminary analysis of surface temperature field evolution with time (for instance acquired by infrared thermography); subsequently, this analysis is improved by taking advantage of a priori information provided by ground-penetrating radar reconstruction of the structure under investigation. In this way, it is possible to improve the accuracy of the images achievable with the standalone thermal reconstruction method in the case of quasiperiodic natural excitation.

show abstract

Section: Coupling Of Thermal and Electromagnetic Methodsmentioning

confidence: 99%

A joint thermal and electromagnetic diagnostics approach for the inspection of thick walls

Touz

Dumoulin

Gennarelli

et al. 2017

Geosci. Instrum. Method. Data Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Based on electromagnetic scattering model, subsurface targets are modelled as Δε( → r ) and the imaging algorithm can be established from electromagnetic scattering integral equation [5][6][7][8][9][10].…”

Section: Open Accessmentioning

confidence: 99%

“…The imaging methods presented in references [7][8][9] all belong to the class of quantitative imaging strategies, that is to say, they aim at reconstructing the dielectric permittivity and electric conductivity of the targets and provide information on their geometrical features. Soldovieri et al faced the problem of embedded rebar localization and transformed it to a linear inverse problem by exploiting the Born scattering model [10]. This inversion method falls within the framework of the sparse minimization and accounts for the sparse nature of the scatterers in the investigated domain by exploiting a distributional representation of the unknown function.…”

Section: Open Accessmentioning

confidence: 99%

A Multi-Scale Weighted Back Projection Imaging Technique for Ground Penetrating Radar Applications

et al. 2014

View full text Add to dashboard Cite

Abstract:In this paper, we propose a new ground penetrating radar (GPR) imaging technique based on multi-scale weighted back projection (BP) processing. Firstly, the whole imaging region is discretized by large scale and low-resolution imaging result is obtained by using traditional BP imaging technique. Secondly, the potential targets regions (PTR) are delineated from low-resolution imaging result by using intensity detection method. In the PTR, small scale discretization is implemented and higher resolution imaging result is obtained by using weighted BP imaging technique. A weight factor is designed by analyzing the statistical characteristics of scattering data on the time-delay curve. The above "discretization-imaging-PTR delineation" processing continues until the imaging resolution reaches the specified requirement. In the multi-scale imaging result, the resolution in other regions is not as high as that in PTR. This algorithm can get higher resolution imaging results with much lower computation compared with traditional BP imaging algorithm. The simulation of this algorithm is processed and experimental results validate the feasibility of this method.

show abstract

“…With the further development of CS theory, considerable work has been done to apply CS to SFGPR system establishment and image reconstruction in order to reduce the data acquisition time and improve the image quality [9][10][11][12][13][14][15][16]. In practical SFGPR measurement situation, since the distance between antennas and ground is very short, the wave reflected from the ground is much stronger than that from underground targets.…”

Section: Introductionmentioning

confidence: 99%

Compressive Sensing SFGPR Imaging Algorithm Based on Subspace Projection Ground Clutter Suppression

Sun¹,

Lu²,

Zhang³

2016

PIER M

View full text Add to dashboard Cite

Abstract-Stepped frequency ground penetrating radar (SFGPR) has received increasing attention in the field of ground penetrating radar technology due to its superiority in the detection performance. Compressed sensing (CS) SFGPR imaging reconstruction method can not merely reduce the measured imaging data volume, but also reconstruct target image with less sidelobe. However, the imaging algorithm using CS approach will lose efficacy in strong clutter environment. To solve this problem, a CS SFGPR imaging reconstruction method combined with subspace projection clutter suppression approach is proposed in this paper. First, all frequency domain data at each measurement position are reconstructed from reduced frequency measurements via sparse reconstruction technique. Then subspace projection ground clutter suppression technique is used to suppress the strong ground clutter. Finally, the orthogonal matching pursuit (OMP) algorithm is utilized to reconstruct the underground target image. Synthetic and experimental data processing results have verified the effectiveness and accuracy of the proposed imaging method.

show abstract

Sparse Reconstruction From GPR Data With Applications to Rebar Detection

Cited by 82 publications

References 16 publications

A joint thermal and electromagnetic diagnostics approach for the inspection of thick walls

A joint thermal and electromagnetic diagnostics approach for the inspection of thick walls

A Multi-Scale Weighted Back Projection Imaging Technique for Ground Penetrating Radar Applications

Compressive Sensing SFGPR Imaging Algorithm Based on Subspace Projection Ground Clutter Suppression

Contact Info

Product

Resources

About