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dc.contributor.authorMennitt, Daniel Jamesen_US
dc.date.accessioned2014-03-14T20:18:32Z
dc.date.available2014-03-14T20:18:32Z
dc.date.issued2008-11-04en_US
dc.identifier.otheretd-11142008-162801en_US
dc.identifier.urihttp://hdl.handle.net/10919/29583
dc.description.abstractWireless sensor networks and data fusion has received increasing attention in recent years, due to the ever increasing computational power, battery and wireless technology, and proliferation of sensor modalities. Notably, the application of acoustic sensors and arrays of sensors has expanded to encompass surveillance, teleconferencing, and sound source localization in adverse environments. The ability to passively locate and track acoustic sources, be they gunfire, animals, or geological events, is crucial to a wide range of applications. The challenge addressed herein is how to best utilize the massive amount of data collected from spatially distributed sensors. Localization in two acoustic propagation scenarios is addressed: the free-field assumption and the general case. In both cases, it is found that performance is highly dependent on the array-source geometry which in turn drives the design of localization strategies. First, the general surveillance problem including signal detection, classification, data association, localization and tracking is studied. Signal detectors are designed with a focus on robustness and capacity for real time implementation. Specifics of the data association problem relevant to acoustic measurements are addressed. Assuming free-field propagation, a localization algorithm is developed to harness some of the vast potential and robust nature of a sensor networks. In addition, a prototypical sensor network has been constructed to accompany the theoretical development, address real world situations, and demonstrate applicability. Experimental results obtained confirm the practicality of theoretical models, support numerical results, and illustrate the effectiveness of the proposed strategies and the system as a whole. In many situations of interest, obstacles to wave propagation such as terrain or buildings exist that provide unique challenges to localization. These obstacles introduce multiple paths, diffraction, and scattering into the propagation. The second part of this dissertation investigates localization in the general propagation scenario of a multi-wave, semi-reverberant environment characteristic of urban areas. Matched field processing is introduced as a feasible method and found to offer superior performance and flexibility over time reversal techniques. The effects of uncertainty in model parameters are studied in an urban setting. Multiarray processing methods are developed and strategies to mitigate the effects of model mismatch are established.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartDissertation_vF.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectNumerical Modelingen_US
dc.subjectSignal Classificationen_US
dc.subjectMatched Field Processingen_US
dc.subjectSensor Networksen_US
dc.subjectAcoustic Localizationen_US
dc.titleMultiarray Passive Acoustic Localization and Trackingen_US
dc.typeDissertationen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeememberKurdila, Andrew J.en_US
dc.contributor.committeememberRoan, Michael J.en_US
dc.contributor.committeememberWoolsey, Craig A.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11142008-162801/en_US
dc.contributor.committeecochairJohnson, Martin E.en_US
dc.contributor.committeecochairCarneal, James P.en_US
dc.date.sdate2008-11-14en_US
dc.date.rdate2008-12-11
dc.date.adate2008-12-11en_US


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