为提高相机内参数标定的精度，减小角点坐标估计不精确带来的误差，提出了一种亚像素迭代角点优化算法，通过对相机成像进行建模，融合畸变数学模型，并使用亚像素迭代算法，计算搜索窗口内点的梯度值变化，迭代优化角点坐标，为标定提供更为精确的初值，结合优化后的角点坐标，利用张氏标定法，求解内参数，实验验证并讨论角点数对角点采集和相机标定的影响，并用重投影误差表征标定精度，将所提算法与其他算法进行对比，对迭代算法的有效性进行验证。实验结果表明：在使用算法后，迭代30次即可获得稳定结果，误差相较于无迭代算法降低77%，可有效提高相机内参数标定精度，降低迭代次数，减少运行时间。

In order to improve the accuracy of in-camera parameter calibration and reduce the error caused by inaccurate estimation of corner coordinates, a subpixel iterative corner optimization algorithm was proposed. By modeling the camera image, integrating the distortion mathematical model, and using the subpixel iterative algorithm, the gradient value changes of points in the search window were calculated and the corner coordinates were iteratively optimized to provide more accurate initial values for calibration. Combining with the optimized corner coordinates, Zhang's calibration method was used to solve the internal parameters, and the influence of corner points on the acquisition of diagonal points and camera calibration was discussed through experiments. The calibration accuracy was characterized by reprojection error, and the effectiveness of the iterative algorithm was tested. The experimental results show that the algorithm can effectively improve the accuracy of corner acquisition and the calibration accuracy of camera parameters by using fewer iterations.