On improving the performance of the Gauss-Newton filter

 

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dc.contributor.advisor Inggs, Michael en_ZA
dc.contributor.author Nadjiasngar, Roaldje en_ZA
dc.date.accessioned 2014-07-31T10:54:25Z
dc.date.available 2014-07-31T10:54:25Z
dc.date.issued 2013 en_ZA
dc.identifier.citation Nadjiasngar, R. 2013. On improving the performance of the Gauss-Newton filter. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/5142
dc.description Includes abstract.
dc.description Includes bibliographical references.
dc.description.abstract The Gauss-Newton filter is a tracking filter developed by Norman Morrison around the same time as the celebrated Kalman filter. It received little attention, primarily due to the computation requirements at the time. Today computers have vast processing capacity and computation is no-longer an issue. The filter finite memory length is identified as the key element in the Gauss-Newton filter adaptability and robustness. This thesis focuses on improving the performance of the Gauss-Newton. We incorporate the process noise statistics into the filter algorithm to obtain a filter which explains the error covariance inconsistency of the Kalaman filter. In addition, a biased version of the linear Gauss-Newton filter, with lower mean squared error than the unbiased filter, is proposed. Furthermore the Gauss-Newton filter is adapted using the Levenberg Marquardt method for improved convergence. In order to improve the computation requirements, a recursive version of the filter is obtained. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Electrical Engineering en_ZA
dc.title On improving the performance of the Gauss-Newton filter en_ZA
dc.type Thesis / Dissertation en_ZA
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Engineering & the Built Environment en_ZA
dc.publisher.department Department of Electrical Engineering en_ZA
dc.type.qualificationlevel Doctoral en_ZA
dc.type.qualificationname PhD en_ZA
uct.type.filetype Text
uct.type.filetype Image


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