AUTHOR: MBAOCHA CHRISTIAN CHIDIEBERE PhD
DEPARTMENT: ELECTRICAL ELECTRONICS ENGINEERING
AFFILIATION: FEDERAL UNIVERSITY OF TECHNOLOGY OWERRI
Satellite attitude determination methods usually fall in one of two classes: point-by-point and recursive estimation algorithms. Point-by-point attitude determination is based on the measurements of two or more sensors in a single point in time, while recursive estimation uses information from successive time points, as well as knowledge about the spacecraft dynamic and/or kinematics models. In small satellites, a single attitude sensor is often available, due to cost and space constraints, thus leading to the exploration of recursive estimation based solutions, such as the Kalman Filter. Because of the constraints presented by the size and capabilities of the sensors, actuators and micro-controllers used in micro-satellites, it is often difficult to process the Extended Kalman filter algorithm used in larger satellite mission. This work adopts a linearization technique that reduced considerably the processing time requirement of the Extended Kalman Filter algorithm. The non-linear system of estimator was modelled using Euler angles parameterisation which is applicable for real-time operation onboard-satellite. The developed filtering estimator was tested through simulated data and the result obtained showed adequate performance.
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