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Rami S. Mangoubi, Roger M. Hain and Zaichun Feng. Dever, Christopher W. (Christopher Walden), 1972- Massachusetts Institute of Technology. Department of Mechanical Engineering 2009-10-01T15:44:45Z 2009-10-01T15:44:45Z 1998 1998 http://hdl.handle.net/1721.1/47801 42900298 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998. Includes bibliographical references (p. 166-170) and index. This thesis investigates the use of vehicle model-based filtering for spacecraft attitude determination. Whereas traditional navigation filters typically rely only on the kinematic relations between body rate and attitude in their filter designs, the state estimator presented here expands the plant model to include rigid body effects and disturbance torques. When rate sensing gyroscope measurement error components are large, as is anticipated in the new generation of micromechanical inertial sensors, the model-based approach provides superior performance to the standard kinematic designs. The estimation performance gains, which include enhanced attitude tracking of several tenths of a degree and closed-loop control stabilization, are most apparent when external attitude data becomes sparse. Even if the gyroscope measurement quality were to improve, for some satellite missions the possibility of an external measurement outage still necessitates vehicle dynamic modeling for greater gyro bias observability. The thesis also gives insight into robustness measures to compensate for model uncertainty, disturbance torque estimation, and GPS multipath error mitigation. by Christopher W. Dever. S.M. 172 p. eng Massachusetts Institute of Technology M.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. http://dspace.mit.edu/handle/1721.1/7582 Mechanical Engineering Vehicle model-based filtering for spacecraft attitude determination Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="0bf44920-0f7f-4656-97c7-8095a6c58fe4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Vehicle model-based filtering for spacecraft attitude determination</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>1998</PublicationDate> <Authors> <Author> <DisplayName>Dever, Christopher W. (Christopher Walden), 1972-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Mechanical Engineering</Keyword> <Abstract>This thesis investigates the use of vehicle model-based filtering for spacecraft attitude determination. Whereas traditional navigation filters typically rely only on the kinematic relations between body rate and attitude in their filter designs, the state estimator presented here expands the plant model to include rigid body effects and disturbance torques. When rate sensing gyroscope measurement error components are large, as is anticipated in the new generation of micromechanical inertial sensors, the model-based approach provides superior performance to the standard kinematic designs. The estimation performance gains, which include enhanced attitude tracking of several tenths of a degree and closed-loop control stabilization, are most apparent when external attitude data becomes sparse. Even if the gyroscope measurement quality were to improve, for some satellite missions the possibility of an external measurement outage still necessitates vehicle dynamic modeling for greater gyro bias observability. The thesis also gives insight into robustness measures to compensate for model uncertainty, disturbance torque estimation, and GPS multipath error mitigation.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>