LAUSR

Under high dynamic and long exposure conditions, the number of recognized stars on motion-blurred star images decreases, thereby degrading the attitude accuracy of star sensors. To improve the attitude accuracy, a restoration method based on multi-frame superposition, which focuses on the noise removal and quality of restored star images, is proposed for a star sensor. During each short exposure time, the corrected coordinate variation of the same star spot between adjacent star images is determined using a motion recursive model. Subsequently, the corrected star spot region is obtained, and the noise is removed. A restoration algorithm based on multi-frame superposition is proposed, taking the time consumption and quality of restored star image considered simultaneously. Simulation results indicate that the proposed restoration method based on multi-frame superposition is effective in removing noise and improving the quality of restored star images. The star recognition rate in simulation experiments verifies the advantages of the proposed method.