Airborne photoelectric platform has a wide application prospect in the field of imaging, especially in the field of UAV reconnaissance. However, in the process of image acquisition, the photoelectric platform equipment will produce obvious image shift because of its own attitude change
or speed instability, so it is necessary to compensate the collected image. In this study, when the image motion compensation is carried out, the internal and external parameters of the camera are adjusted, and the geometric model of the image is established. The Camera Calibration Toolbox
provided by MatLab is used to calibrate the internal parameters of camera. At the same time, when obtaining the camera's internal parameters, the corresponding flight attitude angle is obtained with the aid of the inertial navigation system. At the same time of acquiring the attitude of the
aircraft by hardware, it is necessary to obtain the image shift coefficient by using the function. The coordinate system needs to be transformed into a coordinate system suitable for the inertial navigation system, so as to facilitate the calculation of external parameters of the camera. The
transformation matrix from image moving image to normal image can be established by obtaining the parameters inside and outside the camera. Through bilinear interpolation, the matrix is derived in MatLab environment. In the experiment, 16 black-and-white grid images are selected to obtain
the attitude angle, so as to complete the calculation process of the conversion matrix. Then, the images with image shift are screened out from the images taken in aerial state. The method proposed in this study is used for image compensation. According to the root mean square error analysis,
the image compensation scheme proposed in this study is helpful to the imaging application of UAV airborne platform.
Improved motor control method with measurements of fiber optics gyro (FOG) for dual-axis rotational inertial navigation system (RINS)
