Abstract

To perform efficient on-orbit calibration for star cameras, we developed an attitude-independent calibration approach for global optimization and noise removal by least-square estimation using multiple star images, with which the optimal principal point, focal length, and the high-order focal plane distortion can be obtained in one step in full consideration of the interaction among star camera parameters. To avoid the problem when stars could be misidentified in star images, an iteration method with variable weights is introduced to eliminate the influence of misidentified star pairs. The approach can increase the precision of least-square estimation and use fewer star images. The proposed approach has been well verified to be precise and robust in three experiments.

© 2015 Optical Society of America

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