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Attitude Estimation for a Deorbiter CubeSat
Institute for Aerospace Studies, University of Toronto, Toronto, Canada.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Institute for Aerospace Studies, University of Toronto, Toronto, Canada.ORCID iD: 0000-0003-4977-6339
2019 (English)In: Proceedings of 9th International Conference on Recent Advances in Space Technologies: RAST 2019 / [ed] S. Menekay; O. Cetin; O. Alparslan, IEEE, 2019, p. 709-714Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates the attitude estimation capabilities of a debris-removing nanosatellite called deorbiter CubeSat. The spacecraft is designed based on the utilization of commercially-available components with long space heritage, which are embedded in an eight-unit form factor. The attitude estimation machinery employed in this work is a discrete-time, quaternion-based, extended Kalman filter, which utilizes measurements provided by a three-axis rate sensor, five sun sensors, and a three-axis magnetometer. To obtain a linear state-space model, gravity gradient and magnetic disturbance torques are included in the plant model, and the model is linearized with respect to the process noise and the states, namely the inertial angular velocities and the quaternions. measurements noises are modelled based on zero-mean Gaussian distributions, and are quantified based on the performance of the state-of-the-art, commercial-of-the-shelf devices. A Monte Carlo simulation is created to analyze the performance of the estimator against various initial angular velocities and quaternions, both in the sunlit and in the eclipsed portions of the orbit. In light of the results, the accuracy of the deorbiter CubeSat’s attitude knowledge is discussed.

Place, publisher, year, edition, pages
IEEE, 2019. p. 709-714
Keywords [en]
attitude estimation, extended Kalman filter, normconstrained EKF, deorbiter CubeSat
National Category
Control Engineering
Research subject
Onboard space systems
Identifiers
URN: urn:nbn:se:ltu:diva-85975DOI: 10.1109/RAST.2019.8767789ISI: 000492052500116Scopus ID: 2-s2.0-85073902392OAI: oai:DiVA.org:ltu-85975DiVA, id: diva2:1572937
Conference
9th International Conference on Recent Advances in Space Technologies (RAST 2019), Istanbul, Turkey, June 11-14, 2019
Note

ISBN för värdpublikation: 978-1-5386-9448-0

Available from: 2021-06-24 Created: 2021-06-24 Last updated: 2024-03-07Bibliographically approved

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Emami, M. Reza

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