Camera pose estimation is widely used in computer vision and robotics. Aiming at the stability and real-time performance of camera pose estimation, a camera pose estimation algorithm considering the uncertainty of spatial reference points based on orthogonal iterative algorithm is proposed. The key idea of the algorithm is to obtain the weights of the corresponding feature points in consideration of camera distortion and use an accelerated orthogonal iterative algorithm to regularize the repeated calculations in the iterative process. And the camera pose is obtained by minimizing the weighted re-projection object residual function. Results of simulation data experiments and real image experiment show that the proposed algorithm has higher calculation accuracy, faster speed, and lower time complexity. In the case of deep spatial feature points or the feature points deviating from the optical axis of the camera, the time complexity and accuracy of the algorithm are better than the existing orthogonal iterative algorithms, indicating its feasibility in the real-time estimation of camera pose.