Pose estimation in monocular vision is a key problem in three-dimensional measurement, which is widely used in machine vision, precision measurement and so on. This problem can be solved by n-point perspective (PnP) algorithm. Orthogonal iterative algorithm (OI), as the representative of PnP algorithm, has been widely used in practice because of its high precision. In order to further improve the robustness and computational efficiency of OI algorithm, a weighted accelerated orthogonal iterative algorithm (WAOI) is proposed in this paper. Firstly, the weighted orthogonal iterative algorithm is deduced according to the classical orthogonal iterative algorithm. The weighted collinearity error function is constructed and the weight is updated by using the object point reprojection error to achieve the purpose of iteratively optimizing the pose estimation results. Secondly on this basis, through adaptive weights, the calculation of translation vector and objective function in each iteration is integrated to reduce the amount of calculation in the iterative process, so as to accelerate the algorithm. The experimental results show that when there are two rough points in the 12 reference points, the reprojection accuracy of the reference point of WAOI is 0.64 pixel, the operation time is 8.02 ms, the accuracy is high and the running speed is fast, so it has strong engineering practical value.