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dc.contributor.advisorMortari, Daniele
dc.creatorSpratling, Benjamin
dc.date.accessioned2012-07-16T15:56:18Z
dc.date.accessioned2012-07-16T20:22:12Z
dc.date.available2012-07-16T15:56:18Z
dc.date.available2012-07-16T20:22:12Z
dc.date.created2011-05
dc.date.issued2012-07-16
dc.date.submittedMay 2011
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2011-05-8926
dc.description.abstractIn order to perform star-identification with lower processing requirements, multi-dimensional techniques are implemented in this research as a database search as well as to create star pattern parameters. New star pattern parameters are presented which produce a well-distributed database, required by the database search algorithm to achieve the fastest performance. To mitigate problems introduced by the star pattern selection, incorrect entries are added to the database, which reduces the number of iterations of the run-time algorithm. The associated algorithms, star pattern parameters, and database preparation are collectively referred to as Multi-dimensional Star-Identification (Star-ND). The star pattern parameters developed may also be extended to star patterns with an arbitrarily large number of stars, while retaining the well-distributed property. The algorithm is contrasted with the current state-of-the-art star-ID algorithm, Pyramid. The database is found to grow linearly with the size of the star catalog, while Pyramid's database grows quadratically. The running time of Star-ND is found to be on average a factor of 25 times faster than the time for Pyramid.en
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectstar identificationen
dc.titleStar-ND (Multi-Dimensional Star-Identification)en
dc.typeThesisen
thesis.degree.departmentAerospace Engineeringen
thesis.degree.disciplineAerospace Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberReed, Helen L.
dc.contributor.committeeMemberJunkins, John L.
dc.contributor.committeeMemberFriesen, Donald
dc.type.genrethesisen
dc.type.materialtexten


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