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dc.contributor.advisorThompson, Michael Wayne.
dc.creatorStone, Joshua Dale.
dc.date.accessioned2016-06-21T13:42:30Z
dc.date.available2016-06-21T13:42:30Z
dc.date.created2016-05
dc.date.issued2016-05-05
dc.date.submittedMay 2016
dc.identifier.urihttp://hdl.handle.net/2104/9608
dc.description.abstractBearings-only localization is a problem with applications in the communications and defense sectors. Although the problem of point estimation for bearings-only localization has been well explored in the literature, there still exists a significant need for methods for interval estimation, particularly methods which are non-parametric in nature. This thesis applies a non-parametric statistical technique called the empirical bootstrap to accomplish two goals. The first is the application of the bootstrap to develop a novel, non-iterative, asymptotically unbiased estimator for bearings-only localization. The second is a method which leverages the bootstrap, as well as the aforementioned estimator, to estimate two-dimensional confidence ellipses for bearings-only localization. The development of these techniques is supported by simulation study over a range of scenario geometries and noise models, and the results are shown to be competitive to current techniques, if not preferable, depending on the particular problem domain and situation.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectBearings-only localization. Bootstrap. Estimation. Non-parametric methods. Signal processing.
dc.titleMethod for the application of the empirical bootstrap to confidence ellipse estimation in bearings-only localization.
dc.typeThesis
dc.rights.accessrightsWorldwide access.
dc.rights.accessrightsAccess changed 7/12/18.
dc.type.materialtext
thesis.degree.nameM.S.E.C.E.
thesis.degree.departmentBaylor University. Dept. of Electrical & Computer Engineering.
thesis.degree.grantorBaylor University
thesis.degree.levelMasters
dc.date.updated2016-06-21T13:42:30Z
local.embargo.lift2018-05-01
local.embargo.terms2018-05-01


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