在相机位姿估计的实际应用中,参考点的坐标数据不可避免地包含了测量误差,其量值大小通常不会完全一致,如果不区别测量误差直接进行相机位姿估计,将可能导致估计结果与真值相差甚远。为此,在广泛应用的正交迭代算法基础上,提出了相机位姿估计的加权正交迭代算法,该方法以加权共线误差为目标函数,根据像面重投影误差确定权重系数取值,优化相机位姿估计结果,具有精度高、稳健性好等优点,且满足全局收敛条件。数值仿真实验与风洞迎角实验的结果表明,本文算法更加有效,能够抑制不同程度测量误差对相机位姿估计结果的影响,所得结果明显优于正交迭代算法,具有较强的工程实用价值。

In the practical applications for camera pose estimation, the coordinates of reference points inevitably contain measurement errors, and the magnitude of the errors will not always be the same. If the camera pose is estimated directly without distinguishing the errors, the estimation result may be very different from the true value. Therefore, the weighted orthogonal iterative algorithm is proposed based on the widely used orthogonal iterative algorithm. In this algorithm, the weighted collinear error is taken as the objective function. In each iteration, the weight coefficients are determined according to the re-projection errors in image, and the camera pose estimation results are optimized by the coefficients. This algorithm satisfies the conditions of global convergence, and has the advantages of high precision and good robustness. The experimental results show that the proposed algorithm is effective. The estimation results of the proposed algorithm are significantly better than those of the orthogonal iterative algorithm, when the coordinates of reference points contain different errors. It shows that the proposed algorithm has strong engineering practical values.