Robust adaptive detection of buried pipes using GPR

Hoarau, Quentin; Ginolhac, Guillaume; Atto, Abdourrahmane M.; Nicolas, Jean‐Marie; Ovarlez, Jean‐Philippe

doi:10.1109/eusipco.2016.7760305

Cited by 6 publications

(1 citation statement)

References 29 publications

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“…Table 3 summarizes the different algorithms' research papers related to the detection process. [18] A powerful ground-penetrating radar detector was developed using the Adaptive Normalized Match Filter (ANMF) to detect buried tubes. The electromagnetic wave (EMW) signal is sent directly to the ground.…”

Section: Detection Of Buried Objects Based On Ground-penetratingmentioning

confidence: 99%

Different techniques in detection of buried objects using ground-penetrating radar: A review

shamy

Sadah

Saeed

2022

QJES

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This literature reviews the work of researchers on ground-penetrating radar (GPR). This research consists of five sections starting from the first section that focuses on the general application and the advantage of the GPR system in comparison to other types of underground detection systems. The main function of the GPR system is to detect the object buried underground and at the end of the full scan, the output image represents the total signals detected by the receiver of the GPR device. One of the main applications of the GPR system is the detection of an underground object, the GPR scans the underground area and the output image represents the total of the signals detected by the receiver. The second section discusses methods for removing unwanted signals such as noise and direct waves from the output image of a GPR system. After removing the noise, the image requires further analysis to discover and interpret the buried object. The third section discusses the common methods used in the process of identifying buried objects. There are different types of buried objects and section four discusses the algorithms used to detect and identify landmines and explosive devices. Finally, the last section summarizes the paper that discussed the detection and identification process using smart algorithm technology. These types of algorithms are the most accurate, have a lower error rate and are cost-effective.

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Section: Detection Of Buried Objects Based On Ground-penetratingmentioning

confidence: 99%

Different techniques in detection of buried objects using ground-penetrating radar: A review

shamy

Sadah

Saeed

2022

QJES

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A subspace approach for shrinkage parameter selection in undersampled configuration for Regularised Tyler Estimators

Hoarau

Breloy

Ginolhac

et al. 2017

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Regularized Tyler Estimator's (RTE) have raised attention over the past years due to their attractive performance over a wide range of noise distributions and their natural robustness to outliers. Developing adaptive methods for the selection of the regularisation parameter α is currently an active topic of research. Indeed, the bias-performance compromise of RTEs highly depends on the considered application. Thus, finding a generic rule that is optimal for every criterion and/or data configurations is not straightforward. This issue is addressed in this paper for undersampled configurations (number of samples lower than the dimension of the data). The paper proposes a new regularisation parameter selection based on a subspace reduction approach. The performance of this method is investigated in terms of estimation accuracy and for adaptive detection purposes, both on simulation and real data.

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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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Robust adaptive detection of buried pipes using GPR

Cited by 6 publications

References 29 publications

Different techniques in detection of buried objects using ground-penetrating radar: A review

Different techniques in detection of buried objects using ground-penetrating radar: A review

A subspace approach for shrinkage parameter selection in undersampled configuration for Regularised Tyler Estimators

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

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