In the task of camera pose estimation, the measurement of the position of the reference point is easily affected by the measuring instrument or the environment, leading a certain degree of measurement error. And the larger error point has a great influence on the final solution accuracy, which is called the outliers. Aiming at the problem that the existing algorithms have weak ability to resist outliers, a fast camera pose estimation algorithm based on measurement error uncertainty weighting is proposed. Based on the classic orthogonal iterative algorithm, the algorithm introduces M estimation method, assigns the corresponding weight to the objective function according to the measurement error of the reference point, eliminates the influence of the outlier point to the greatest extent, and introduces the Kronecker product to optimize the calculation process. Thus the redundant calculations in the iterative process are reduced and the calculation speed is increased. The simulation results show that the improved algorithm not only improves the anti-outliers ability of the original algorithm, but also realizes faster calculation speed.