Abstract: As a critical technology in the aerospace field, estimating the relative position and attitude of satellite solar panels is crucial for successfully executing on-orbit satellite maintenance missions. However, under complex lighting conditions in space, nonuniform illumination and interference from repetitive edge textures complicate the accurate extraction of solar panel feature points, thereby impacting the precision of relative position and attitude estimation. Therefore, a method for estimating the relative positions and attitudes of satellite solar panels under complex lighting conditions through robust feature-point extraction was proposed. This method began by accurately segmenting the solar panel areas using a lightweight, multiscale edge-guided network. After preprocessing the segmentation results, the edges were fitted to straight lines, and the intersection points of these lines were calculated to efficiently extract the feature points of the solar panels.Based on this information, the relative position and attitude parameters of the solar panels were determined by matching point pairs based on adjacent frame data. Experimental results demonstrate that, under complex lighting conditions, as the camera dynamically approaches from a distance of 60 to 15 m, the proposed method effectively maintained the relative attitude error within 2° and reduced the relative position error from 0.38 to 0.04 m,highlighting its high precision and robustness.

Key words: image segmentation, feature point extraction, satellite solar panels, position and attitude estimation