A Visual-Inertial attitude propagation for resource constrained small satellites
An accurate and efficient attitude determination system is a key component for Earth-observation small satellites. However, most of the small satellites operate without redundant attitude sensors due to the satellite’s small form factor and are therefore at a significant risk of mission failure. In this research, we propose a visual-inertial attitude propagation approach for Earth-observation small satellites. The proposed approach integrates vision-based and inertial attitude estimation methods in an unscented Kalman filter (UKF) framework. The vision-based method propagates attitude in three degrees of freedom from sequentially captured images based on Earth-observation geometrical constraints and total shift correction method. For validation of the vision-based method’s performance, we used raw imagery data of High Definition Earth Viewing (HDEV) payload of the International Space Station (ISS). The performance of the visual-inertial approach is assessed through the realistic Earth-surface scene simulations and results are compared with ground truth data.
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