Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System

Differential evolution (DE) algorithm, which is a global convergence algorithm, is often used to estimate the position of underground targets detected with a portable transient electromagnetic (TEM) system. The DE algorithm is extremely time-consuming due to thousands of iterations. A new algorithm...

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Autores principales:	Lijie Wang, Shuang Zhang, Shudong Chen, Hejun Jiang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Transient electromagnetic (TEM) unexploded ordnance (UXO) magnetic gradient tensor Gaussian-Newton algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/031323b6877e4cfca15d297c47b7a91f
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id	oai:doaj.org-article:031323b6877e4cfca15d297c47b7a91f
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spelling	oai:doaj.org-article:031323b6877e4cfca15d297c47b7a91f2021-11-18T00:10:14ZFast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System2169-353610.1109/ACCESS.2021.3124285https://doaj.org/article/031323b6877e4cfca15d297c47b7a91f2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9594808/https://doaj.org/toc/2169-3536Differential evolution (DE) algorithm, which is a global convergence algorithm, is often used to estimate the position of underground targets detected with a portable transient electromagnetic (TEM) system. The DE algorithm is extremely time-consuming due to thousands of iterations. A new algorithm for fast localization of an underground target by magnetic gradient tensor and Gaussian-Newton algorithm with a portable TEM system is proposed. First, the gradient tensor of an underground target is constructed with the differential responses received by the portable sensor. Gradient tensor, commonly used in magnetic detection, is applied for the first time in TEM detection to estimate the target position for each measurement. Then, all the estimated positions are averaged to reduce the localization error. Taking the averaged position as the initial value, the Gaussian-Newton algorithm can complete iterations within dozens of times, which can effectively improve the speed and accuracy of the algorithm. Finally, the performance of the new method has been verified in the test-stand and field experiments. Results show that the errors of averaged positions by gradient tensor are no more than 8 cm in the horizontal direction. The errors of the estimated positions, inclination, and rotation angles by the Gaussian-Newton algorithm are no more than 4 cm, 6°, and 5°, respectively. The statistical running time of the proposed method takes approximately tens of milliseconds, accounting for about 7% of the DE algorithm. The proposed method can achieve fast and accurate localization and characterization of targets and has an important significance to the digging and recognition of underground targets.Lijie WangShuang ZhangShudong ChenHejun JiangIEEEarticleTransient electromagnetic (TEM)unexploded ordnance (UXO)magnetic gradient tensorGaussian-Newton algorithmElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 148469-148478 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Transient electromagnetic (TEM) unexploded ordnance (UXO) magnetic gradient tensor Gaussian-Newton algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Transient electromagnetic (TEM) unexploded ordnance (UXO) magnetic gradient tensor Gaussian-Newton algorithm Electrical engineering. Electronics. Nuclear engineering TK1-9971 Lijie Wang Shuang Zhang Shudong Chen Hejun Jiang Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
description	Differential evolution (DE) algorithm, which is a global convergence algorithm, is often used to estimate the position of underground targets detected with a portable transient electromagnetic (TEM) system. The DE algorithm is extremely time-consuming due to thousands of iterations. A new algorithm for fast localization of an underground target by magnetic gradient tensor and Gaussian-Newton algorithm with a portable TEM system is proposed. First, the gradient tensor of an underground target is constructed with the differential responses received by the portable sensor. Gradient tensor, commonly used in magnetic detection, is applied for the first time in TEM detection to estimate the target position for each measurement. Then, all the estimated positions are averaged to reduce the localization error. Taking the averaged position as the initial value, the Gaussian-Newton algorithm can complete iterations within dozens of times, which can effectively improve the speed and accuracy of the algorithm. Finally, the performance of the new method has been verified in the test-stand and field experiments. Results show that the errors of averaged positions by gradient tensor are no more than 8 cm in the horizontal direction. The errors of the estimated positions, inclination, and rotation angles by the Gaussian-Newton algorithm are no more than 4 cm, 6°, and 5°, respectively. The statistical running time of the proposed method takes approximately tens of milliseconds, accounting for about 7% of the DE algorithm. The proposed method can achieve fast and accurate localization and characterization of targets and has an important significance to the digging and recognition of underground targets.
format	article
author	Lijie Wang Shuang Zhang Shudong Chen Hejun Jiang
author_facet	Lijie Wang Shuang Zhang Shudong Chen Hejun Jiang
author_sort	Lijie Wang
title	Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
title_short	Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
title_full	Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
title_fullStr	Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
title_full_unstemmed	Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System
title_sort	fast localization of underground targets by magnetic gradient tensor and gaussian-newton algorithm with a portable transient electromagnetic system
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/031323b6877e4cfca15d297c47b7a91f
work_keys_str_mv	AT lijiewang fastlocalizationofundergroundtargetsbymagneticgradienttensorandgaussiannewtonalgorithmwithaportabletransientelectromagneticsystem AT shuangzhang fastlocalizationofundergroundtargetsbymagneticgradienttensorandgaussiannewtonalgorithmwithaportabletransientelectromagneticsystem AT shudongchen fastlocalizationofundergroundtargetsbymagneticgradienttensorandgaussiannewtonalgorithmwithaportabletransientelectromagneticsystem AT hejunjiang fastlocalizationofundergroundtargetsbymagneticgradienttensorandgaussiannewtonalgorithmwithaportabletransientelectromagneticsystem
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Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System

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