基于精密测角法的测绘相机分组渐进标定算法

针对精密测角法标定测绘相机内方位元素中理论误差和观测点分布状态对标定精度影响的问题，提出了一种基于精密测角法的分组渐进标定算法。提出的算法包括2个部分：采用分组渐近方式调整精密转台零点位置，减小了理论误差；对每组观测数据引入了数据一致性约束，消除观测值分布、数量对标定结果的影响。最后，给出了分组渐进算法的精度分析。实验数据显示，在相同试验环境条件下，分组渐进标定算法中主点、主距标定精度比精密测角算法分别提高了2.43倍和2.00倍，可达到2.12 μm和4.02 μm，表明分组渐进标定算法提高了标定精度。

Grouped Approach Algorithm for Mapping Camera Calibration Based on Method of Exact Measuring Angle

Toward the problems of theoretical error and the distribution status of the observed which can influence on camera calibration accuracy, a grouped approach algorithm based on exact measuring angle method is proposed. The proposed algorithm is composed of two parts: the method of adjusting the zero point of precise rotating platform is put forward to reduce the theoretical error, and the method of weighted theory is used to approach group data processing to eliminate the influence on the calibration result. Finally, the accuracy of grouped approach algorithm is analyzed. Experimental results show that principal point accuracy and the principal distance accuracy obtained by the proposed algorithm are reduced to 2.12 μm and 4.02 μm and improved by 2.43 times and 2.00 times respectively, comparing with the traditional exact measuring angle method in the same laboratory environment. The experimental results indicate that the calibration accuracy has been improved greatly.