GPR-Based Landmine Detection and Identification Using Multiple Features

This paper presents a method to identify landmines in various burial conditions. A ground penetration radar is used to generate data set, which is then processed to reduce the ground effect and noise to obtain landmine signals. Principal components and Fourier coefficients of the landmine signals ar...

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Main Authors: Kwang Hee Ko, Gyubin Jang, Kyungmi Park, Kangwook Kim
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2012/826404
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spelling doaj-c094b4c133674dd2b03b42c8afbce8582020-11-24T21:01:40ZengHindawi LimitedInternational Journal of Antennas and Propagation1687-58691687-58772012-01-01201210.1155/2012/826404826404GPR-Based Landmine Detection and Identification Using Multiple FeaturesKwang Hee Ko0Gyubin Jang1Kyungmi Park2Kangwook Kim3The School of Mechatronics, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of KoreaThe School of Mechatronics, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of KoreaThe School of Mechatronics, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of KoreaThe School of Mechatronics, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, Republic of KoreaThis paper presents a method to identify landmines in various burial conditions. A ground penetration radar is used to generate data set, which is then processed to reduce the ground effect and noise to obtain landmine signals. Principal components and Fourier coefficients of the landmine signals are computed, which are used as features of each landmine for detection and identification. A database is constructed based on the features of various types of landmines and the ground conditions, including the different levels of moisture and types of ground and the burial depths of the landmines. Detection and identification is performed by searching for features in the database. For a robust decision, the counting method and the Mahalanobis distance-based likelihood ratio test method are employed. Four landmines, different in size and material, are considered as examples that demonstrate the efficiency of the proposed method for detecting and identifying landmines.http://dx.doi.org/10.1155/2012/826404
collection DOAJ
language English
format Article
sources DOAJ
author Kwang Hee Ko
Gyubin Jang
Kyungmi Park
Kangwook Kim
spellingShingle Kwang Hee Ko
Gyubin Jang
Kyungmi Park
Kangwook Kim
GPR-Based Landmine Detection and Identification Using Multiple Features
International Journal of Antennas and Propagation
author_facet Kwang Hee Ko
Gyubin Jang
Kyungmi Park
Kangwook Kim
author_sort Kwang Hee Ko
title GPR-Based Landmine Detection and Identification Using Multiple Features
title_short GPR-Based Landmine Detection and Identification Using Multiple Features
title_full GPR-Based Landmine Detection and Identification Using Multiple Features
title_fullStr GPR-Based Landmine Detection and Identification Using Multiple Features
title_full_unstemmed GPR-Based Landmine Detection and Identification Using Multiple Features
title_sort gpr-based landmine detection and identification using multiple features
publisher Hindawi Limited
series International Journal of Antennas and Propagation
issn 1687-5869
1687-5877
publishDate 2012-01-01
description This paper presents a method to identify landmines in various burial conditions. A ground penetration radar is used to generate data set, which is then processed to reduce the ground effect and noise to obtain landmine signals. Principal components and Fourier coefficients of the landmine signals are computed, which are used as features of each landmine for detection and identification. A database is constructed based on the features of various types of landmines and the ground conditions, including the different levels of moisture and types of ground and the burial depths of the landmines. Detection and identification is performed by searching for features in the database. For a robust decision, the counting method and the Mahalanobis distance-based likelihood ratio test method are employed. Four landmines, different in size and material, are considered as examples that demonstrate the efficiency of the proposed method for detecting and identifying landmines.
url http://dx.doi.org/10.1155/2012/826404
work_keys_str_mv AT kwangheeko gprbasedlandminedetectionandidentificationusingmultiplefeatures
AT gyubinjang gprbasedlandminedetectionandidentificationusingmultiplefeatures
AT kyungmipark gprbasedlandminedetectionandidentificationusingmultiplefeatures
AT kangwookkim gprbasedlandminedetectionandidentificationusingmultiplefeatures
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