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dc.contributor.authorGürkan, Serkan
dc.contributor.authorKarapınar, Mustafa
dc.contributor.authorDoğan, Seydi
dc.date.accessioned2020-12-09T11:46:50Z
dc.date.available2020-12-09T11:46:50Z
dc.date.issued2019en_US
dc.identifier.issn2076-3417
dc.identifier.urihttps://doi.org/10.3390/app9245415
dc.identifier.urihttps://hdl.handle.net/20.500.12462/10919
dc.descriptionDoğan, Seydi (Balikesir Author)en_US
dc.description.abstractActive and passive techniques are two different techniques with which to detect buried explosives. In practice, the most preferred active method works by broadcasting a signal underground. This signal may stimulate the buried explosive and cause it to explode. It is important to eliminate or minimize this drawback to ensure the safety of the detector operator. In this respect, it is important to increase the studies on the passive detection technique which is not currently used in practice. The aim of this study was to passively detect improvised explosive devices without stimulating them, and to classify underground objects as explosive or non-explosive. A fluxgate sensor array having 33 components was used for passive magnetic field measurements, and the nearest neighborhood algorithm was preferred for classifying the resulting data. In experimental studies, 33 different samples having different amounts of ferromagnetic properties were used. Successful imaging and classification were achieved for the measurements up to 20 cm below the surface of soil. Data were recorded as 32 x 25 matrices, and then they were reduced to 32 x 2 matrices having the same features. Samples having explosive properties were distinguished from other underground objects with success rates of 86% and 95% for 32 x 25 and 32 x 2 data matrices, respectively. Classification times for 32 x 25 and 32 x 2 data matrices were 42 ms and 3.62 ms, respectively. For data groups where the best results were obtained for the data matrices, frame numbers classified in one second were calculated as 23.80 and 276.2, respectively. False alarm rate achieved was 5.31%. The experimental results proved the successes of the matrices reduction and classification approach. One of the most common problems encountered in passive detecting techniques is that the sensor position affects the measurements negatively. In this paper, a solution has been proposed for this important problem.en_US
dc.description.sponsorshipBalikesir University 2016/103 Turkish Academy of Sciencesen_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.relation.isversionof10.3390/app9245415en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectUnderground object detectionen_US
dc.subjectMagnetic field measurementen_US
dc.subjectNearest neighbor searchesen_US
dc.subjectRemote sensingen_US
dc.titleDetection and imaging of underground objects for distinguishing explosives by using a fluxgate sensor arrayen_US
dc.typearticleen_US
dc.relation.journalApplied Sciences-Baselen_US
dc.contributor.departmentMühendislik Fakültesien_US
dc.contributor.authorID0000-0003-2229-3361en_US
dc.contributor.authorID0000-0001-9785-4990en_US
dc.identifier.volume9en_US
dc.identifier.issue24en_US
dc.identifier.startpage1en_US
dc.identifier.endpage18en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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