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Adaptive iteration method for star centroid extraction under highly dynamic conditions

Star centroiding accuracy decreases significantly when star sensor works under highly dynamic conditions or star images are corrupted by severe noise, reducing the output attitude precision. Herein, an adaptive iteration method is proposed to solve this problem. Firstly, initial star centroids are predicted by traditional method, and then based on initial reported star centroids and angular velocities of the star sensor, adaptive centroiding windows are generated to cover the star area and then an iterative method optimizing the location of centroiding window is used to obtain the final star spot extraction results. Simulation results shows that, compared with traditional star image restoration method and Iteratively Weighted Center of Gravity method, AWI algorithm maintains higher extraction accuracy when rotation velocities or noise level increases.