Jiang Linyi, Li Xiaoyan, Li Liyuan, Yang Lin, Yang Lan, Hu Zhuoyue, Chen Fansheng
Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences, Shanghai 200083, China.
CAS Key Laboratory of Infrared System Detection and Imaging Technology, Shanghai Institute of Technical Physics, Shanghai 200083, China.
Sensors (Basel). 2021 Oct 7;21(19):6668. doi: 10.3390/s21196668.
Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.
在发射和轨道穿透过程中，受振动和热冲击的影响，地面测量的遥感相机的几何定位模型会产生位移，影响图像的几何精度，需要重新校准。传统方法采用地面控制点（GCP）或恒星作为在轨几何校准的参考。然而，不可避免的云层覆盖和不尽人意的提取算法使得收集足够的高精度GCP来修正相机的对准误差极其困难，特别是对于地球静止卫星。此外，观测到的恒星数量很可能不足以校准相机的相对安装。针对上述问题，我们提出了一种利用恒星相对运动对地球静止相机进行在轨几何校准的新方法。首先，基于光学系统结构构建几何校准模型。然后，分析观测恒星的相对运动变换。利用恒星轨迹和辅助星历获得相应的目标向量，迭代修正相关校准参数。基于地球静止实验卫星数据的实验结果表明，该方法校正后的定位误差可控制在±2.35像素以内。该方法能够有效校准相机，提高定位精度，避免了云层覆盖的影响，克服了对观测恒星数量的极大依赖。
