摆扫航空大视场红外扫描仪具有视场角大、分辨率高等优点，但因在传感器安装、运输、飞行时会受到抖动的影响，常导致传感器的中心、安置角度发生偏移。因此有必要对CCD影像进行几何外检校，以提高传感器影像的几何质量。特别是此类扫描仪不同摆扫方向会对成像质量造成不同影响，因此本文针对航空大视场红外扫描仪成像特点，构建了考虑左、右摆扫不同影响的几何外检校模型。该检校模型具有如下特点：（1）左、右摆影像同时检校，并分别设置不同的安置参数矩阵。扫描仪的左、右摆扫会造成成像积分方向的不同，进而导致左、右摆影像定位精度的不一致，因此利用不同的左、右摆参数矩阵，消除摆扫角误差对成像几何精度造成的影响。（2）增加检校参数伪观测方程。由于该航空大视场红外扫描仪存在大摆扫角，随着摆扫角的变化，相机与定位定姿系统安置误差检校参数间可能存在较强相关性，因此引入检校参数伪观测方程。实验结果表明该检校模型能有效提升影像的几何定位精度，检校后左右摆影像反投影偏差降低到亚像素水平。

Objective: The airborne pendulum large-view-field infrared scanner has the advantages of large view field and high-resolution images. However, it may be affected by a variety of factors in the sensor installation, transportation and flight processes, which may cause the position centers and angles of the sensor and the POS system to be changed. Therefore, it is necessary to carry out geometric calibration to improve the geometric quality of the images acquired by the sensor. Furthermore, this scanner produces left-pendulum and right-pendulum images respectively during the flight. And the left-pendulum and right-pendulum images have different imaging integration direction, which may cause different influence on imaging quality. Therefore, the purpose of this paper is to present an external geometric calibration method considering different influences of the different pendulum directions. Method: By considering different influences of the different pendulum directions of this airborne pendulum large-view-field infrared scanner, a geometric external calibration model is introduced, and it is characterized by: (1) The installation errors of the sensor and POS are considered. And both of the left- and right- pendulum images are used to calculate the installation parameters. Especially, different calibration parameters are used for the right- and left- pendulum images. The aim is to compensate the different influences caused by different imaging integration directions. (2) Furthermore, calibration parameters for the installation errors of the sensor and POS are regarded as pseudo-observations. Because the installation errors of the sensor and POS are generally small. By regarding the calibration parameters as the pseudo-observations, the calibration model can avoid very large unreasonable estimated parameters. Results and conclusions: The proposed method is applied in the calibration of the images collected by this airborne pendulum large-view-field infrared scanner. Experimental results show that the calibration model can effectively improve the geometric positioning accuracy of the images. The absolute average back-projection residuals of the control points in the left- and right- pendulum images are improved to be sub-pixel level.