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dc.contributor.advisorRobert Haupt and Arthur Baggeroer.en_US
dc.contributor.authorDoherty, John Houstonen_US
dc.contributor.otherWoods Hole Oceanographic Institution.en_US
dc.date.accessioned2009-06-30T17:12:00Z
dc.date.available2009-06-30T17:12:00Z
dc.date.copyright2008en_US
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/46058
dc.descriptionThesis (S.M.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2008.en_US
dc.descriptionIncludes bibliographical references (p. 54-56).en_US
dc.description.abstractLandmines and mine-like traps are effective weapons that are difficult to detect and discriminate from a safe distance. The ability to detect landmines in their host environment at a distance and to discriminate them from other objects would be valuable for countering the landmine threat. This paper explores a standoff acoustic/laser technique to discriminate landmines from other forms of man-made objects (clutter) in an urban environment. A novel approach currently under investigation by MIT Lincoln Labs, University of Mississippi, and other groups employs a non-contact acoustic/laser technique to detect landmines from a safe standoff range. This technique uses a sound source to excite vibrations in targets with an acoustic wave. These vibrations are in turn measured remotely with a Laser Doppler Vibrometer (LDV). In this thesis, the vibration responses of landmine variants are measured, analyzed, and compared to those of common urban objects likely to be found on a landmine field or roadside. The Fourier Transform of the vibration of the target as measured by the LDV is used to generate a target vibration spectrum. Target vibration spectra in response to a sound source were experimentally measured for 59 trials, 28 of which were of simulated landmine variants and the remaining trials were of urban clutter objects. Using an algorithm adapted from a methodology for mass spectral analysis, parameters of the target signatures are estimated; then individual target signatures are classified using a Support Vector Machine (SVM) with a training set composed of parameters from the remaining members of the total population. The best results obtained from this methodology had a 71% probability of detection and a 3% false alarm rate corresponding to 20 of 28 of the simulated landmine variants correctly identified and a single clutter object misidentified as a landmine variant.en_US
dc.description.statementofresponsibilityby John Houston Doherty.en_US
dc.format.extent120 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subject/Woods Hole Oceanographic Institution. Joint Program in Oceanography/Applied Ocean Science and Engineering.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectWoods Hole Oceanographic Institution.en_US
dc.subject.lcshSound-wavesen_US
dc.subject.lcshSolids Acoustic propertiesen_US
dc.titleLandmine detection with a standoff acoustic/laser techniqueen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentJoint Program in Oceanography/Applied Ocean Science and Engineeringen_US
dc.contributor.departmentWoods Hole Oceanographic Institutionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc374152656en_US


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