We propose a standalone monocular visual Simultaneous Localization and Mapping (vSLAM) initialization pipeline for autonomous robots in space. Our method, a state-of-the-art factor graph optimization pipeline, enhances classical Structure from Small Motion (SfSM) to robustly initialize a monocular agent in weak-perspective projection scenes. Furthermore, it overcomes visual estimation challenges introduced by spacecraft inspection trajectories, such as: center-pointing motion, which exacerbates the bas-relief ambiguity, and the presence of a dominant plane in the scene, which causes motion estimation degeneracies in classical Structure from Motion (SfM). We validate our method on realistic, simulated satellite inspection images exhibiting weak-perspective projection, and we demonstrate its effectiveness and improved performance compared to other monocular initialization procedures.