Microwave Tomography for the Inspection of Wood Materials: Imaging System and Experimental Results

Boero, Federico; Fedeli, Alessandro; Lanini, Matteo; Maffongelli, Manuela; Monleone, Ricardo; Pastorino, Matteo; Randazzo, Andrea; Salvade, Andrea; Sansalone, Andrea

doi:10.1109/tmtt.2018.2804905

Cited by 63 publications

(54 citation statements)

References 50 publications

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“…Electromagnetic waves at the microwave spectrum allow to get high resolution. That is why over the years a great deal of research has been carried out to tackle the many challenges of subsurface imaging, both in terms of the system and the imaging algorithms [15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Subsurface Detection of Shallow Targets by Undersampled Multifrequency Data and a Non-Cooperative Source

et al. 2019

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Imaging buried objects embedded within electrically large investigation domains can require a large number of measurement points. This is impractical if long data acquisition time cannot be tolerated or the system is conceived to work at some stand-off distance from the air/soil interface; for example, if it is mounted over some flying platform. In order to reduce the number of spatial measurements, here, we propose a method for detecting and localizing shallowly buried scattering targets from under-sampled far-field data. The method is based on a scattering model derived from the equivalence theorem for electromagnetic radiation. It exploits multi-frequency data and does not require that the transmitter and receivers are synchronized, making the source non-cooperative. To provide a benchmark against which spatial data have to be reduced, first, the number of required spatial measurements is examined by analyzing the properties of the relevant scattering operator. Then, since under-sampling data produces aliasing artifacts, frequency diversity (i.e., multi-frequency data) is exploited to mitigate those artifacts. In particular, single-frequency reconstructions are properly fused and a criterion for selecting the frequencies to be used is provided. Numerical examples show that the method allows for satisfactory target transverse localization with a number of measurements that are much less than the ones required by other methods commonly used in subsurface imaging.

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Section: Introductionmentioning

confidence: 99%

Subsurface Detection of Shallow Targets by Undersampled Multifrequency Data and a Non-Cooperative Source

et al. 2019

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“…Moreover, in the solution of problem (2), constraints were enforced on the admissible EPs values of the investigated region being tested in order to get permittivity values higher than 1 and conductivity values higher than 0. In the following text, two relevant examples are presented in order to give a proof of the performance achievable by means of M-DIVE, both dealing with heterogeneous profiles coming from two real applications involving complex scenarios-that is, breast phantom imaging [29][30][31] and tree trunk inspection [32][33][34].…”

Section: Breast Phantom Imagingmentioning

confidence: 99%

“…The tree being tested was a four-layered oak phantom with dielectric properties fixed by following References [32,40]. In particular, the inner heartwood layer had ε = 9 and σ = 0.005 S/m; the sapwood layer was characterized by ε = 16, σ = 0.01 S/m; next, the thicker layer was the phloem, with ε = 22, σ = 0.05 S/m; finally, the bark had ε = 6.2, σ = 0.02 S/m.…”

Section: Tree Trunk Inspectionmentioning

confidence: 99%

“…The second test case concerns the inspection of wood materials, around which interest has been growing in recent years. The reasons for this are related to the possibility of achieving useful information about the healthy state of standing trees in order to prevent falls and optimize cutting strategies [32][33][34], but also to assess the quality of the wood product in industrial processes [32][33][34]. Moreover, the use of microwaves for these kinds of inspections seems to be attractive with respect to ultrasound or X-ray-based techniques, especially in terms of cost and data acquisition time (see [32][33][34][35] and references therein).…”

Section: Introductionmentioning

confidence: 99%

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Multiresolution Virtual Experiments for Microwave Imaging of Complex Scenarios

2019

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In this paper, a multiresolution approach for the quantitative microwave imaging of complex scenarios is introduced. The proposed strategy takes advantage of the combined use of a recently introduced iterative method known as distorted iterated virtual experiments (DIVE), based on the paradigm of “virtual experiments”, and a wavelet-based projection scheme. This strategy allows the unknown profiles to be represented at different resolution scales and, as such, it is particularly suitable for the imaging of highly heterogeneous targets. Moreover, the developed algorithm blends together the intrinsic multiresolution feature of the wavelet projection with the one gained by means of a frequency hopping technique. The method was tested against realistic heterogeneous scenarios of practical interest, such as breast and tree trunk phantoms, which are of interest in non-invasive medical diagnostics and the health monitoring of standing trees.

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“…This reduces the probability of false arm (PFA). In [19], a new microwave radar imaging prototype has been developed for inspecting wood material. It is based on a set of custom antennas positioned in proximity to the sample, and a hardware design to reconstruct tomographic maps of a wooden slab or a tree trunk.…”

Section: Introductionmentioning

confidence: 99%

Microwave-Based SAR Technique for Pipeline Inspection Using Autofocus Range-Doppler Algorithm

2019

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In non-destructive testing and evaluation, microwave-based synthetic aperture radar (SAR) imaging have shown great potential in the detection of defects on buried objects such as pipes. However, due to pipe curvature and high standoff distance when inspecting an insulated pipe, the useful defect information used to characterise the pipe image is lost as a result of low signal-to-noise ratio (SNR) resulting in a blurred and unfocused image. In this paper, we proposed a robust microwave-based SAR imaging using autofocus range-Doppler algorithm (RDA) for the inspection of an insulated pipe. Singular value decomposition (SVD) is used to mitigate the effect of the insulation layer by removing dominant singular values that characterise the insulation layer, and the autofocus RDA is designed to refocus the SAR image using RDA residual refocusing. SNR, improvement factor (IF) and squared error (SE) are used to evaluate the qualitative image information of the defect on the pipe. Experimental results showed the efficacy of the method in detecting defects on an insulated pipe, in particular, a significant reduction in the noise content of the image compared to the known SAR Omega-k algorithm. It was found that the autofocus RDA gave higher values of SNR and IF (3 dB and 6 dB) compared to the Omega-k algorithm (-1 dB and 2 dB) respectively.

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Microwave Tomography for the Inspection of Wood Materials: Imaging System and Experimental Results

Cited by 63 publications

References 50 publications

Subsurface Detection of Shallow Targets by Undersampled Multifrequency Data and a Non-Cooperative Source

Subsurface Detection of Shallow Targets by Undersampled Multifrequency Data and a Non-Cooperative Source

Multiresolution Virtual Experiments for Microwave Imaging of Complex Scenarios

Microwave-Based SAR Technique for Pipeline Inspection Using Autofocus Range-Doppler Algorithm

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