Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor

The superimposed response of multi-target causes difficulty in locating and characterizing each target when detecting unexploded ordnance with a portable transient electromagnetic sensor, constructed with a single-layer transmitting coil and five three-component receiving coils. Differential evoluti...

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Autores principales:	Shudong Chen, Shuang Zhang, Xinqun Luan, Zhaohe Liu
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2020
Materias:	Unexploded ordnance portable transient electromagnetic sensor differential evolution algorithm Gram–Schmidt orthogonalization multisource model Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/e3b4a911b2d34987ab63c43d25f51dbb
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spelling	oai:doaj.org-article:e3b4a911b2d34987ab63c43d25f51dbb2021-11-20T00:00:36ZImproved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor2169-353610.1109/ACCESS.2020.3038656https://doaj.org/article/e3b4a911b2d34987ab63c43d25f51dbb2020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9261451/https://doaj.org/toc/2169-3536The superimposed response of multi-target causes difficulty in locating and characterizing each target when detecting unexploded ordnance with a portable transient electromagnetic sensor, constructed with a single-layer transmitting coil and five three-component receiving coils. Differential evolution (DE) algorithm is improved here with Gram–Schmidt orthogonalization and position rearrangement for superimposed response inversion based on the multisource model, which represents the multi-target response with a set of magnetic dipoles distributed over the interrogated area. The Gram–Schmidt orthogonalization turns the coefficient matrix of each target into an orthonormal basis. Accordingly, the best magnetic polarization tensor can be directly extracted from the superimposed response without inverting large and potentially ill-conditioned matrices. The position rearrangement groups the positions of individuals in the contemporary population to maximize the likelihood that the positions in the same group belong to the same target. The convergence speed of multi-target inversion is accelerated with the crossover operation of DE algorithm performed within the groups. Simulated experiment results show that the error in estimated position and characteristic response for improved DE algorithm is only 10% of that of the conventional DE algorithm. Field experiment is also conducted, and its results show that the error in estimated position for improved DE algorithm is only 20% of that of the conventional DE algorithm. The improved DE algorithm can accurately estimate the position and characteristic response of each target from superimposed response.Shudong ChenShuang ZhangXinqun LuanZhaohe LiuIEEEarticleUnexploded ordnanceportable transient electromagnetic sensordifferential evolution algorithmGram–Schmidt orthogonalizationmultisource modelElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 8, Pp 208107-208119 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Unexploded ordnance portable transient electromagnetic sensor differential evolution algorithm Gram–Schmidt orthogonalization multisource model Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Unexploded ordnance portable transient electromagnetic sensor differential evolution algorithm Gram–Schmidt orthogonalization multisource model Electrical engineering. Electronics. Nuclear engineering TK1-9971 Shudong Chen Shuang Zhang Xinqun Luan Zhaohe Liu Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
description	The superimposed response of multi-target causes difficulty in locating and characterizing each target when detecting unexploded ordnance with a portable transient electromagnetic sensor, constructed with a single-layer transmitting coil and five three-component receiving coils. Differential evolution (DE) algorithm is improved here with Gram–Schmidt orthogonalization and position rearrangement for superimposed response inversion based on the multisource model, which represents the multi-target response with a set of magnetic dipoles distributed over the interrogated area. The Gram–Schmidt orthogonalization turns the coefficient matrix of each target into an orthonormal basis. Accordingly, the best magnetic polarization tensor can be directly extracted from the superimposed response without inverting large and potentially ill-conditioned matrices. The position rearrangement groups the positions of individuals in the contemporary population to maximize the likelihood that the positions in the same group belong to the same target. The convergence speed of multi-target inversion is accelerated with the crossover operation of DE algorithm performed within the groups. Simulated experiment results show that the error in estimated position and characteristic response for improved DE algorithm is only 10% of that of the conventional DE algorithm. Field experiment is also conducted, and its results show that the error in estimated position for improved DE algorithm is only 20% of that of the conventional DE algorithm. The improved DE algorithm can accurately estimate the position and characteristic response of each target from superimposed response.
format	article
author	Shudong Chen Shuang Zhang Xinqun Luan Zhaohe Liu
author_facet	Shudong Chen Shuang Zhang Xinqun Luan Zhaohe Liu
author_sort	Shudong Chen
title	Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
title_short	Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
title_full	Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
title_fullStr	Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
title_full_unstemmed	Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor
title_sort	improved differential evolution algorithm for multi-target response inversion detected by a portable transient electromagnetic sensor
publisher	IEEE
publishDate	2020
url	https://doaj.org/article/e3b4a911b2d34987ab63c43d25f51dbb
work_keys_str_mv	AT shudongchen improveddifferentialevolutionalgorithmformultitargetresponseinversiondetectedbyaportabletransientelectromagneticsensor AT shuangzhang improveddifferentialevolutionalgorithmformultitargetresponseinversiondetectedbyaportabletransientelectromagneticsensor AT xinqunluan improveddifferentialevolutionalgorithmformultitargetresponseinversiondetectedbyaportabletransientelectromagneticsensor AT zhaoheliu improveddifferentialevolutionalgorithmformultitargetresponseinversiondetectedbyaportabletransientelectromagneticsensor
_version_	1718419869661134848

Improved Differential Evolution Algorithm for Multi-Target Response Inversion Detected by a Portable Transient Electromagnetic Sensor

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