Satellite pose measurement using an improving SIFT algorithm

Due to the strong reflective properties of the spacecraft surface coatings, there are significant challenges in processing images from outer space. Furthermore, the volume of data for image feature processing and matching is immense, and existing algorithms are insufficient for aerospace system applications. Therefore, this paper proposes a three-dimensional pose measurement algorithm based on binocular vision. The binocular vision-based three-dimensional pose measurement system consists of four main components: camera calibration, camera rectification, stereo matching, and pose determination. Traditional image processing algorithms are employed for satellite image processing. Camera calibration is performed using M software, and the calibration results are further optimized. Due to real-time requirements, an improved SIFT algorithm is used to detect local features in the images, extract feature points, and perform feature point matching under epipolar constraints. Experimental results demonstrate that this algorithm can achieve accurate and fast three dimensional pose measurement.