【摘要】 为了提升无人机机载光电吊舱在特殊工况条件下的自主侦察能力，本文结合实际工程项目研发了适用于机载光电吊舱的目标定位技术，并在嵌入式GPU(Graphics Processing Unit，型号为Jetson-TX2i)上实现了功能验证。首先，提出一种改进的SURF(Speeded Up Robust Features)算法与GPU加速数字图像处理方案，对不同焦距下获取的两幅图像进行实时特征检测与匹配。接着，利用几何交比不变性校正图像边缘畸变特征点的位置信息。最后，使用最小二乘法估计目标深度信息并结合四元数空间模型确定目标姿态信息，从而实现目标定位。实验结果表明，改进的SURF算法在特征匹配方面，精度和速度都优于经典的SURF算法。若角点特征位置误差控制在一个像素以内，深度误差不超过2%，方位角、俯仰角和滚转角的角度误差分别小于4°，5°和2°，这一误差满足机载光电吊舱的目标定位准确性需求。此外，处理一组（两帧）分辨率为1080P的图像，利用GPU加速可以将处理时间提升至74 ms，这一速度满足机载光电吊舱数据处理的实时性需求。更多还原

【Abstract】 In order to improve the autonomous detection ability of the airborne optronics pod of a UAV under special working conditions, this paper developed a targeting technology suitable for the airborne optronics pod in an actual engineering project, and realized the functional verification on the embedded GPU(Graphics Processing Unit, Jetson-TX2i platform model). Firstly, we proposed an improved SURF(Speeded Up Robust Features) algorithm and GPU-accelerated digital image processing scheme to detect and match the real-time features of two images acquired at different focal lengths. Secondly, geometric cross-ratio invariance was used to correct the position information of distorted feature points at image edges. Finally, we used the least square method to estimate the depth information of the target and combines the quaternion space model to determine the attitude information of the target to determine its position. Experimental results show that the improved SURF algorithm is superior to the classical SURF algorithm in feature matching accuracy and speed. If the corner characteristic position error is controlled within one pixel, the depth error is no more than 2% and the angle errors of azimuth, pitch and roll angles are less than 4°, 5° and 2°, respectively. This error meets the target positioning accuracy requirements of the airborne optronics pod. In addition, when processing a set of images(two frames) at 1080 P resolution, the processing time can be increased to 74 ms through GPU acceleration, which meets the real-time demand for data processing in the airborne optronics pod.更多还原