2017
DOI: 10.1109/taes.2017.2667458
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Particle Swarm Optimization With Rotation Axis Fitting for Magnetometer Calibration

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Cited by 33 publications
(25 citation statements)
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“…ROTATION TIME ANALYSIS Given a satellite of known mass and moment of inertia along the spin axis, we can compute angular velocity achievable for a spinning spacecraft at a given applied voltage. The estcube and Foresail missions require a high spin rate along major axis of inertia while maintaining the sun pointing [29], [30]. The rotation time analysis was performed for a 1U cube using optimized magnetorquers.…”
Section: Fig 8 Plot Of Operating Voltage Against Torque τ /P Powermentioning
confidence: 99%
See 1 more Smart Citation
“…ROTATION TIME ANALYSIS Given a satellite of known mass and moment of inertia along the spin axis, we can compute angular velocity achievable for a spinning spacecraft at a given applied voltage. The estcube and Foresail missions require a high spin rate along major axis of inertia while maintaining the sun pointing [29], [30]. The rotation time analysis was performed for a 1U cube using optimized magnetorquers.…”
Section: Fig 8 Plot Of Operating Voltage Against Torque τ /P Powermentioning
confidence: 99%
“…The overall temperature for the cubesat can be computed by (29) and (30). The analysis computes the temperature rise due to the printed magnetorquers while neglecting all the other internal heat dissipations.…”
Section: Fig 8 Plot Of Operating Voltage Against Torque τ /P Powermentioning
confidence: 99%
“…Mutation step reduction has a parameter (Δℎ and ) which defines how fast mutation step decreases [9]. Formula for calculating parameter based on final required solution tolerance is:…”
Section: Calibration Algorithmmentioning
confidence: 99%
“…The advantages of this method are simplicity and a lower calculation burden, but it has also the shortcoming of low precision. The particle swarm optimisation algorithm is a new off-line magnetometer calibration method (Wu et al, 2011; Riwanto et al, 2017). It can utilise a more accurate nonlinear model and need not consider the initial estimation parameters.…”
Section: Introductionmentioning
confidence: 99%