Camera-IMU State Estimation and External Parameter Online Calibration Algorithm

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.