Aiming at the low efficiency of traditional orthogonal iterative algorithm, an improved orthogonal iterative algorithm is proposed to measure the pose of space objects based on monocular vision. Firstly, based on the traditional orthogonal iterative algorithm, the translation vector in the iterative process was eliminated. The initial value of the rotation matrix was solved by using the parallel perspective model instead of the weak perspective projection model, so as to accelerate the solution process of the orthogonal iterative algorithm. Secondly, simulation experiments are used to study the effects of the extraction accuracy of the imaging point, the accuracy of three-dimensional coordinate of the space feature point, the calibration accuracy of the camera principal point, the calibration accuracy of the camera focal length and the number of space feature points on the accuracy and efficiency of the algorithm. Based on the results of the simulation experiments, Taguchi method is used to quantitatively analyze the influence of each factor on the accuracy of the algorithm, and find out the factor that has the greatest influence on the accuracy of the improved orthogonal iteration algorithm. Finally, the performance of the proposed improved orthogonal iteration algorithm is tested by the physical experiments. The physical experiments prove that the proposed method is accurate, and takes shorter run time than that of traditional orthogonal iteration algorithm. Based on the results of the orthogonal experiment, the accuracy of the improved orthogonal iteration algorithm could meet different demand of different space task by controlling the different influence factors. © 2021, Science Press. All right reserved.