Toward faster and more accurate star sensors using recursive centroiding and star identification

Abstract

The objective of this research is to study different novel developed techniques for spacecraft attitude determination methods using star tracker sensors. This dissertation addresses various issues on developing improved star
\ntracker software, presents new approaches for better performance of star trackers, and
\nconsiders applications to realize high precision attitude estimates.
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\nStar-sensors are often included in a spacecraft attitude-system instrument suite, where
\nhigh accuracy pointing capability is required. Novel methods for image processing, camera
\nparameters ground calibration, autonomous star pattern recognition, and recursive star
\nidentification are researched and implemented to achieve high accuracy and a high frame
\nrate star tracker that can be used for many space missions. This dissertation presents
\nthe methods and algorithms implemented for the one Field of View 'FOV' StarNavI sensor
\nthat was tested aboard the STS-107 mission in spring 2003 and the two fields of view
\nStarNavII sensor for the EO-3 spacecraft scheduled for launch in 2007. The results of
\nthis research enable advances in spacecraft attitude determination based upon real time
\nstar sensing and pattern recognition. Building upon recent developments in image
\nprocessing, pattern recognition algorithms, focal plane detectors, electro-optics, and
\nmicroprocessors, the star tracker concept utilized in this research has the following key
\nobjectives for spacecraft of the future: lower cost, lower mass and smaller volume,
\nincreased robustness to environment-induced aging and instrument response variations,
\nincreased adaptability and autonomy via recursive self-calibration and health-monitoring
\non-orbit. Many of these attributes are consequences of improved algorithms that are
\nderived in this dissertation.