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dc.contributor.authorCooke, Coreyen_US
dc.date.accessioned2014-03-14T20:44:09Z
dc.date.available2014-03-14T20:44:09Z
dc.date.issued2011-08-11en_US
dc.identifier.otheretd-08242011-012951en_US
dc.identifier.urihttp://hdl.handle.net/10919/34748
dc.description.abstractRadio Tomographic imaging (RTI) is an exciting new field that utilizes a sensor network of a large number of relatively simple radio nodes for inverse imaging, utilizing similar mathematical algorithms to those used in medical imaging. Previous work in this field has almost exclusively focused on device-free object location and tracking. In this thesis, the application of RTI to propagation problems will be studied-- specifically using RTI to measure the strength and location of attenuating objects in an area of interest, then using this knowledge of the shadowing present in an area for radio coverage prediction. In addition to radio coverage prediction, RTI can be used to improve the quality of RSS-based position location estimates. Because the traditional failing of RSS-based multilateration is ranging error due to attenuating objects, RTI has great potential for improving the accuracy of these estimates if shadowing objects are accounted for. In this thesis, these two problems will primarily be studied. A comparison with other inverse imaging, remote sensing, and propagation modeling techniques of interest will be given, as well as a description of the mathematical theory used for tomographic image reconstruction. Proof-of-concept of the efficacy of applying RTI to position location will be given by computer simulation, and then physical experiments with an RTI network consisting of 28 Zigbee radio sensors will be used to verify the validity of these assertions. It will be shown in this thesis that RTI does provide noticeable improvement in RSS-based position location accuracy in cluttered environments, and it produces much more accurate RSS estimates than a standard exponential path-loss model is able to provide.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartCooke_CD_T_2011.pdfen_US
dc.relation.haspartCooke_CD_T_2011_Copyright.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.subjectradio tomographyen_US
dc.subjectlocation estimationen_US
dc.subjectpropagation modelingen_US
dc.subjectattenuation field estimationen_US
dc.titleAttenuation Field Estimation Using Radio Tomographyen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
dc.contributor.committeechairBuehrer, Richard Michaelen_US
dc.contributor.committeememberEllingson, Steven W.en_US
dc.contributor.committeememberPratt, Timothy J.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08242011-012951/en_US
dc.date.sdate2011-08-24en_US
dc.date.rdate2011-09-15
dc.date.adate2011-09-15en_US


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