To improve the target recognition distance of the airborne electro-optical reconnaissance equipment of a UAV, this study has developed a high-speed micro-scanning super-resolution core component based on an actual engineering project. The real-time super-resolution reconstruction algorithm is implemented in the embedded platform GPU-TX2i. First, the micro-scanning super-resolution core component moves according to the preset step size and frequency to obtain a continuous image sequence with sub-pixel deviation. Then, the image super-resolution reconstruction algorithm is used based on probability distribution to process the acquired four continuous images into higher resolution images. The experimental results show that the image sequence output achieved by the detector with a frame rate of 120 fps and a resolution of 640×512 is reconstructed via super-resolution and becomes an image sequence with a frame rate of 30 fps and a resolution of 1 280×1024. After super-resolution reconstruction, the effective spatial resolution of the image is increased by 78.2% and target recognition distance is increased by 43.3%. The reconstruction time of a high-resolution image is approximately 33 ms. Furthermore, the micro-scanning super-resolution core component's micro-scan response time is < 1.0 ms and the accuracy in place is < 0.3 μm (corresponding to approximately 0.03 pixels). These results meet the real-time and precision requirements of airborne electro-optical reconnaissance equipment.