Star Identification Based on Multiframe Star Images Fusion

To improve the performance of star identification under conditions of few observed stars in a star image, a star identification algorithm based on multi-frame star images fusion is proposed. The algorithm first determines the common observed stars in adjacent frames by analyzing the angular distance feature, brightness feature, and neighborhood feature. Subsequently, it fuses the adjacent frame star images based on the common observed stars. Finally, an algorithm based on weighted triangle pattern is employed for the star identification of the fused star image. Experimental results demonstrate that the algorithm maintains an identification rate exceeding 90% even when each frame contains only 3∼4 observed stars, significantly outperforming existing methods and show good robustness against various types of noise.