This paper focuses on the issue of estimating the complete 3D pose of the camera with respect to a potentially textureless object, through model-based tracking. We propose to robustly combine complementary geometrical and color edge- based features in the minimization process, and to integrate a multiple-hypotheses framework in the geometrical edge-based registration phase. In order to deal with complex 3D models, our method takes advantage of GPU acceleration. Promising results, outperforming classical state-of-art approaches, have been obtained for space robotics applications on various real and synthetic image sequences and using satellite mock-ups as targets.