基于稠密时角法的天空背景相机标定技术研究

Denseness Star-Arc Calibration for Sky-Background Survey Camera

标定是利用相机进行测量的重要步骤。标定计算相机的内、外方位元素,直接决定了多目视觉测量的精度。在传统的相机标定中,需要设置一定数量稳定、高精度测量的控制点。而在大视场、天空背景下,无法满足上述布设条件。为了实现高精度的相机标定,提出一种可实现内、外参一体化标定的稠密时角标定技术,该技术利用无人机模拟恒星星体,在相机视场内均匀布设控制点并解算标定参数。在解算过程中,针对无人机RTK精度不稳定性,以及特征点提出可靠性提出了非线性最小二乘牛顿-高斯内插算法(WTLS)并得到较高的标定精度。最后采用视场角为77°×66°的相机数据分析验证,实验表明该方法的标定精度高,标定误差优于0.3°,可有效应用于天空背景的大视场相机标定。

Calibration is one of the core processes in intersection survey.In classic calibration,the calculations of intrinsic and exterior parameters are separately and require amount of stable and static control points.However,in large FOV and sky-background survey camera calibration,above mentioned conditions cannot be satisfied.In this paper,a denseness stararc calibration is proposed.To achieve better results,the WTLS is used to eliminate the influence of error from RTK and UAV identification.To test the performance of the proposed method,cameras with the FOV of 77°×66°are used.And the cameras are set with different pitches and azimuths.Experimental results show that the proposed method is able to gain accurate result.Calibration error is less than 0.3°.