Calibration and Uncertainty Analysis of a Spacecraft Attitude Determination Test Stand

University essay from Luleå tekniska universitet/Rymdteknik

Abstract: Experimental testing of attitude determination systems still plays an important role, despite increasing use of simulations. Testing provides a means to numerically quantify system performance, give confidence in the models and methods, and also discover and compensate for unexpected behaviours and interactions with the attitude determination system. The usefulness of the test results is dependent on an understanding of the uncertainties that contribute to the attitude error. With this understanding, the significance of the results can be assessed, and efforts to reduce attitude errors can be directed appropriately. The work of this thesis is to gain a quantitative understanding of the uncertainties that impact the attitude error of low cost spinning spacecraft using COTS camera (as Sun sensor) and MEMS magnetometer. The sensors were calibrated and the uncertainties in these calibrations were quantified, then propagated through the Triad method to uncertainties in the attitude. It was found that most systematic errors were reduced to negligible levels, except those due to timing latencies. Attitude errors achieved in the laboratory with the experimental setup were around 0.14 degrees (3σ) using either the Triad, q-method or Extended Kalman Filter with a gyro for dynamic model replacement. The errors in laboratory were dominated by magnetometer noise. Furthermore, correlated systematic errors had the effect of reducing the attitude error calculated in the laboratory. For an equivalent Sun-mag geometry in orbit, simulation showed that total attitude error would be of the order of 0.77 degrees (3σ). An uncertainty contribution analysis revealed this error was dominated by uncertainties in the inertial magnetic field model. Uncertainties in knowledge of the inertial Sun model, sensor calibration, sensor alignment and sensor noise were shown to be insignificant in comparison.

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