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The accuracy of star centroid extraction for star sensor is decreased in the stray light background due to the gray gradients of the star image, a star centroid extraction algorithm based on background removal by least square method is proposed. Firstly, the influence of stray light background on star centroid extraction is analyzed, and the result shows that the systematic error of star centroid extraction is proportion to the background gray gradients. In order to reduce the systematic error, the least square method is used to fit the window edge pixels to obtain the stray light background image, and then the star centroid is extracted through threshold centroid algorithm after removing the stray light background of the star image. The accuracy of star centroid extraction algorithm is simulated through the practical stray light background images. Compared with the traditional threshold centroid algorithm, the systematic error of star centroid extraction can be reduced from 0.021 pixels to 0.002 pixels. The validity of the algorithm is verified by field star observing experiments for star sensor at Xinglong observation station, and the angular distance of the navigation stars is measured and compared with the Hipparcos catalogue. The systematic error of angular distance is reduced from 0.307″ to 0.013″ after the stray light background has been removed by least square method while the operation time is only increased by 6.3%, which can meet the engineering requirements.
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