Session
Session VIII: Advanced Technologies 2 - Research & Academia
Location
Salt Palace Convention Center, Salt Lake City, UT
Abstract
Given the growing demand for high data rate transmission on small satellites like CubeSats, free-space optical communication terminals have recently attracted an increasing interest thanks to their capability of ensuring high data rates, compact designs and low power requirements. Yet, the performances of the acquisition and pointing processes crucially depend on their attitude knowledge information. This information is currently available only if an optical link has already been established. Nevertheless, it is likewise important to accurately know the attitude during the link acquisition phase to shorten the search time until the opposing target is found. This aspect is equally relevant in the context of Inter-Satellite Links between CubeSats and for enhancing Direct-To-Earth communications.
Indeed, this work presents an attitude estimation concept for CubeSats housing Laser Communication Terminals (LCT), aiming to augment the system’s attitude knowledge to establish optical links and maintain them over time.
Linear extrapolation and quaternion kinematics propagation have been initially investigated for a basic estimation relying on the CubeSat’s ADCS telemetry. Hence a more sophisticated algorithm has been developed consisting of a USQUE Unscented Kalman Filter according to the model of Crassidis and Markley, 2003. This proposed algorithm relies on the attitude information given by the CubeSat’s ADCS as well as on the measurements coming from the LCT’s sensors. A comparative analysis between the algorithms has been undertaken for a dynamic and a stable scenarios in terms of pointing accuracy to investigate the improvement achieved by exploiting the Kalman filter and the information of the LCT.
From simulations, the Kalman filter-based estimation algorithms proved to grant a fast convergence and an accurate estimation of the CubeSat’s attitude. Thanks to this augmented knowledge that relies on the LCT information, it is hence possible to shorten the search time needed to establish an optical link and to easily compensate for pointing errors during the tracking phase of the mission.
Document Type
Event
Augmenting Attitude Knowledge for Optical Communication Terminals on CubeSats by Kalman Filter Based Estimation
Salt Palace Convention Center, Salt Lake City, UT
Given the growing demand for high data rate transmission on small satellites like CubeSats, free-space optical communication terminals have recently attracted an increasing interest thanks to their capability of ensuring high data rates, compact designs and low power requirements. Yet, the performances of the acquisition and pointing processes crucially depend on their attitude knowledge information. This information is currently available only if an optical link has already been established. Nevertheless, it is likewise important to accurately know the attitude during the link acquisition phase to shorten the search time until the opposing target is found. This aspect is equally relevant in the context of Inter-Satellite Links between CubeSats and for enhancing Direct-To-Earth communications.
Indeed, this work presents an attitude estimation concept for CubeSats housing Laser Communication Terminals (LCT), aiming to augment the system’s attitude knowledge to establish optical links and maintain them over time.
Linear extrapolation and quaternion kinematics propagation have been initially investigated for a basic estimation relying on the CubeSat’s ADCS telemetry. Hence a more sophisticated algorithm has been developed consisting of a USQUE Unscented Kalman Filter according to the model of Crassidis and Markley, 2003. This proposed algorithm relies on the attitude information given by the CubeSat’s ADCS as well as on the measurements coming from the LCT’s sensors. A comparative analysis between the algorithms has been undertaken for a dynamic and a stable scenarios in terms of pointing accuracy to investigate the improvement achieved by exploiting the Kalman filter and the information of the LCT.
From simulations, the Kalman filter-based estimation algorithms proved to grant a fast convergence and an accurate estimation of the CubeSat’s attitude. Thanks to this augmented knowledge that relies on the LCT information, it is hence possible to shorten the search time needed to establish an optical link and to easily compensate for pointing errors during the tracking phase of the mission.
