Pose(relative attitude and position) estimation is one of the key technologies in space missions, such as on-orbit servicing, rendezvous and docking, etc. One of the most efficient way to solve this problem is observation on the target by monocular vision such as single CCD measurement. Aiming at the pose estimation of space target based on feature points, an iteration algorithm using obverse projection and orthogonal Procrustes analysis was introduced. Turning the original pose estimation problem to a standard form of orthogonal Procrustes problem, the orthogonal Procrustes problem was solved in the way of successive projection. The key of successive projection method was optimized the attitude matrix row by row. Each row can be solved as a least square problem constrained by a quadratic equation. This algorithm has a global updating and result will be given when errors are within permission. At last, under the background of pose estimation between non-cooperative spacecraft, the simulation experiment shows that this algorithm has both fast convergence speed and strong robustness.