Star map matching method for optical circular rotation imaging based on graph neural networks

This paper focuses on a dynamic star image acquisition and matching method for space situational awareness, which can quickly search for widely distributed resident space objects. First, the optical circular rotation imaging method performed by a single space camera is proposed to obtain a series of star images. And then, the image matching method based on graph neural networks is proposed for generating a wide observation star image. Experiment results show that compared with baseline matching algorithms, the matching accuracy and matching precision of the proposed algorithm are improved significantly.