In this paper, a multi-optical platform target recognition theory based on geocentric observation is proposed by studying the space debris observation model based on multiple optical platforms, and the recognition rate is over 85%. The Gaussian minimum mean square error differential correction algorithm is used to realize the target location by multiple optical observations, and the positioning accuracy reaches 14m, and the positioning accuracy tends to the accuracy of the satellite itself. It can get rid of the disadvantage that the space debris cannot be located by single optical platform, and retain its important advantages such as high accuracy and low power consumption. which lays a solid foundation for the later debris orbit determination.
In this paper, a full information vector recognition algorithm for moving targets is proposed on the basis of the characteristic distribution of point targets and the moving characteristic between frames. The traditional multi -frame image fusion method of moving target recognition is abandoned. We utilize the distribution characteristic of point targets extracted from single image and moving characteristic of point targets extracted from multiple images to recognize and classify moving targets with the similarity principle of feature vector. Compared with the traditional maximum likelihood estimation image processing algorithm, the proposed recognition method costs less computation and provides a novel approach for spatial moving target detection and recognition.