针对影像实时动态测量设备中相机和惯性测量单元（IMU）相对位置发生变化时，需要重新进行外参标定的问题，提出了一种Camera-IMU外参在线标定方法，能够在机械构型未知的情况下自动估计初始值和外参数。首先，使用全球卫星导航时间对齐IMU和相机的时间戳，通过奇异值分解求解旋转量的超定线性方程，改变阈值判定条件和加权方式，减少方程中的退化运动，并剔除外点，提高系统鲁棒性与外参精度，从而获得恒定的Camera-IMU旋转外参。然后基于获得的Camera-IMU旋转外参，固定滑动窗口，利用高斯牛顿法估计Camera-IMU的外参平移量。与原有在线标定方法相比，旋转外参标定方法的精度提高15%，平移外参的精度提高35%，实验结果表明所提方法是有效的。

In this study, we aim to solve the recalibration of the external parameters owing to the changing relative positions of the camera and inertial measurement unit (IMU) in real-time dynamic imaging equipment. Thus, we propose a highly robust Camera-IMU external parameter online calibration method, which automatically estimates the initial value and external parameters when the mechanical configuration is unknown. The global satellite navigation time is used to align the timestamps of the IMU and camera. Then, the singular value decomposition method is used to solve the overdetermined linear equation of rotation. The threshold determination condition and weighting method are modified to reduce degenerate motion in the equation and eliminate the external points, improve system robustness and external parameter accuracy, and obtain constant Camera-IMU rotation external parameters. Then, based on the obtained Camera-IMU rotation external parameters, the sliding window is fixed and the Gaussian-Newton method is used to estimate the Camera-IMU external parameter translation. Compared with the original online calibration method, the calibration accuracy of the rotating external parameter is increased by 15% and the accuracy of the translation external parameters is improved by 35%. Experimental results show the effectiveness of the proposed method.