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dc.contributor.advisorKerri L. Cahoy.en_US
dc.contributor.authorMarlow, Weston Alan Navarroen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.date.accessioned2016-12-05T19:55:18Z
dc.date.available2016-12-05T19:55:18Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/105621
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 123-128).en_US
dc.description.abstractCubeSats are a specific subset of nanosatellites, and their common form factor and canisterized deployers have made it possible to undertake higher risk, lower cost missions that can supplement the current generation of large, monolithic, expensive satellites. Our objective in this thesis is to improve attitude estimation on CubeSats using Unscented Kalman filters. CubeSats have evolved from their relatively low complexity and low computational power beginnings. This progression motivates us to revisit attitude determination estimation approaches commonly used for CubeSats, and to implement an alternative Kalman filtering method. Our goal is to improve the current state of the art in attitude estimation on previous MIT Space Systems Laboratory CubeSats by at least two orders of magnitude from about 1-5* attitude knowledge error down to 0.050 or better. This improvement benefits applications that require precise pointing, such as imaging and active tracking of specific targets, laser communications, and coordinated activity and observations among multiple CubeSats. We were able to achieve better than our pointing error goal of 0.05', and found that the proposed Unscented Kalman filter performed significantly better at high angular rate estimation than the Extended Kalman filter (already implemented on some CubeSats). The quaternion estimates were converted to Euler angles to improve ease of interpretation. For the majority of the missions, the mean total Euler angle estimation error improvement ranged from 83% - 98% with error variance decreased by as much as 98%. One implementation had more than a two order of magnitude improvement, to achieve 0.01* mean error, better than the desired pointing accuracy. We present a detailed assessment of these estimation errors, along with changes in quaternion error that accompany varying the unscented filter parameters.en_US
dc.description.statementofresponsibilityby Weston Alan Navarro Marlow.en_US
dc.format.extent128 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectAeronautics and Astronautics.en_US
dc.titleImproving attitude determination and control of resource-constrained CubeSats using unscented Kalman filteringen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.identifier.oclc962735507en_US


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