A daytime star sensor is a high precision attitude measurement instrument with the ability of detecting stars in the atmosphere during daytime. Different from star sensor applied in space, the performance of daytime star sensor is greatly affected by the strong sky background radiation. The complex and low signal to noise ratio daytime star image increases the difficulties of star recognition. This paper proposes a novel star extraction method for daytime star sensor, mainly focusing on star image preprocessing and fake star removal algorithm. Firstly, an improved morphology Top-Hat filter is provided to suppress the image noise. Then, the detailed process of star extraction is discussed and a pipeline filter is used to reject fake stars. Finally, multi-frame star vectors are calculated and averaged to improve the accuracy. An experiment with daytime star images captured by a self-developed airborne star sensor are analyzed to confirm the validity of the proposed approach, stars can be identified even if there are thin clouds in the sky.
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