Pose estimation of CubeSats via sensor fusion and Error-State Extended Kalman Filter

Fuente: arXiv
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Auteurs principaux: Parikh, Deep, Majji, Manoranjan
Format: Preprint
Publié: 2024
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author Parikh, Deep
Majji, Manoranjan
author_facet Parikh, Deep
Majji, Manoranjan
contents A pose estimation technique based on error-state extended Kalman that fuses angular rates, accelerations, and relative range measurements is presented in this paper. An unconstrained dynamic model with kinematic coupling for a thrust-capable satellite is considered for the state propagation, and a pragmatic measurement model of the rate gyroscope, accelerometer, and an ultra-wideband radio are leveraged for the measurement update. The error-state extended Kalman filter framework is formulated for pose estimation, and its performance has been analyzed via several simulation scenarios. An application of the pose estimator for proximity operations and scaffolding formation of CubeSat deputies relative to their mother-ship is outlined. Finally, the performance of the error-state extended Kalman filter is demonstrated using experimental analysis consisting of a 3-DOF thrust cable satellite mock-up, rate gyroscope, accelerometer, and ultra-wideband radar modules.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10815
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Pose estimation of CubeSats via sensor fusion and Error-State Extended Kalman Filter
Parikh, Deep
Majji, Manoranjan
Systems and Control
A pose estimation technique based on error-state extended Kalman that fuses angular rates, accelerations, and relative range measurements is presented in this paper. An unconstrained dynamic model with kinematic coupling for a thrust-capable satellite is considered for the state propagation, and a pragmatic measurement model of the rate gyroscope, accelerometer, and an ultra-wideband radio are leveraged for the measurement update. The error-state extended Kalman filter framework is formulated for pose estimation, and its performance has been analyzed via several simulation scenarios. An application of the pose estimator for proximity operations and scaffolding formation of CubeSat deputies relative to their mother-ship is outlined. Finally, the performance of the error-state extended Kalman filter is demonstrated using experimental analysis consisting of a 3-DOF thrust cable satellite mock-up, rate gyroscope, accelerometer, and ultra-wideband radar modules.
title Pose estimation of CubeSats via sensor fusion and Error-State Extended Kalman Filter
topic Systems and Control
url https://arxiv.org/abs/2409.10815