Abstract Traditional camera and millimeter-wave radar joint calibration methods have the problem of cumbersome data collection as they can only calibrate on a fixed plane. A fast calibration improvement method applicable to three-dimensional space is proposed based on the traditional methods. Firstly, radar and image preprocessing are performed. Secondly, a time synchronization strategy is used to collect and match a large amount of data within a short period. Then, the random sample consensus algorithm (RANSAC) is used in spatial calibration to reduce the interference of outliers and achieve preliminary coarse calibration. Finally, the Levenberg-Marquardt (LM) algorithm is used to refine the coarse calibration results for precise calibration iteratively. Experimental results show that the improved calibration method converges to an overall root mean square error of about 10 pixels, significantly improving the calibration accuracy compared to traditional joint calibration algorithms, and the calibration process takes about 12 minutes to complete.
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2024, Vol. 45 
