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Approaches to Multiple-source Localization and Signal Classification

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dc.contributor.authorReed, Jesseen
dc.contributor.committeecochairda Silva, Claudio R. C. M.en
dc.contributor.committeecochairBuehrer, R. Michaelen
dc.contributor.committeememberReed, Jeffrey H.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:37:54Zen
dc.date.adate2009-06-10en
dc.date.available2014-03-14T20:37:54Zen
dc.date.issued2009-05-05en
dc.date.rdate2012-04-12en
dc.date.sdate2009-05-21en
dc.description.abstractSource localization with a wireless sensor network remains an important area of research as the number of applications with this problem increases. This work considers the problem of source localization by a network of passive wireless sensors. The primary means by which localization is achieved is through direction-finding at each sensor, and in some cases, range estimation as well. Both single and multiple-target scenarios are considered in this research. In single-source environments, a solution that outperforms the classic least squared error estimation technique by combining direction and range estimates to perform localization is presented. In multiple-source environments, two solutions to the complex data association problem are addressed. The first proposed technique offers a less complex solution to the data association problem than a brute-force approach at the expense of some degradation in performance. For the second technique, the process of signal classification is considered as another approach to the data association problem. Environments in which each signal possesses unique features can be exploited to separate signals at each sensor by their characteristics, which mitigates the complexity of the data association problem and in many cases improves the accuracy of the localization. Two approaches to signal-selective localization are considered in this work. The first is based on the well-known cyclic MUSIC algorithm, and the second combines beamforming and modulation classification. Finally, the implementation of a direction-finding system is discussed. This system includes a uniform circular array as a radio frequency front end and the universal software radio peripheral as a data processor.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-05212009-163628en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05212009-163628/en
dc.identifier.urihttp://hdl.handle.net/10919/33081en
dc.publisherVirginia Techen
dc.relation.haspartThesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectMultiple-Source Localizationen
dc.subjectSource Classificationen
dc.subjectDirection Findingen
dc.subjectMUSICen
dc.subjectcyclic MUSICen
dc.subjectModulation Classificationen
dc.subjectSingle-Source Localizationen
dc.subjectData Associationen
dc.titleApproaches to Multiple-source Localization and Signal Classificationen
dc.typeThesisen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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