Attitude Estimation of On-Orbit Spacecraft Based on the U-Linked Network

Real-time attitude estimation of on-orbit spacecraft is a core task in various space applications. Most of the existing methods are based on long-term observation by high-resolution sensors, such as space-borne cameras and ground-based radars. However, when the observation period is limited, it is difficult to obtain target instantaneous attitude information by these methods. To achieve instantaneous attitude estimation from a single camera image, a U-linked network (ULNet) is proposed in this work. The prior structural constraints of key points are used to reflect the relationship between 3-D target attitude parameters and 2-D images. In this way, target attitude estimation can be solved through the feature point regression when the large-perspective image dataset can be built. The simulation results confirm the feasibility of the proposed method. Besides, the estimation performance of the proposed method also is investigated under different imaging observation conditions.