In this paper, we consider a new unmanned aerial vehicle (UAV)-assisted oblique image acquisition system where a UAV is dispatched to take images of multiple ground targets (GTs). To study the three-dimensional (3D) UAV trajectory design for image acquisition, we first propose a novel UAV-assisted oblique photography model, which characterizes the image resolution with respect to the UAV's 3D image-taking location. Then, we formulate a 3D UAV trajectory optimization problem to minimize the UAV's traveling distance subject to the image resolution constraints. The formulated problem is shown to be equivalent to a modified 3D traveling salesman problem with neighbourhoods, which is NP-hard in general. To tackle this difficult problem, we propose an iterative algorithm to obtain a high-quality suboptimal solution efficiently, by alternately optimizing the UAV's 3D image-taking waypoints and its visiting order for the GTs. Numerical results show that the proposed algorithm significantly reduces the UAV's traveling distance as compared to various benchmark schemes, while meeting the image resolution requirement.
翻译:在本文中,我们考虑一种新的无人驾驶飞行器(UAV)辅助斜面图像采集系统,即派遣无人驾驶飞行器拍摄多个地面目标(GTs)的图像。为了研究用于获取图像的三维(3D)无人驾驶飞行器轨迹设计,我们首先提出一个新的UAV辅助斜面摄影模型,该模型为无人驾驶飞行器3D图像摄像位置的图像解析特征提供了特征。然后,我们制定了3D无人驾驶飞行器轨迹优化问题,以尽量减少无人驾驶飞行器在图像解像限制下的旅行距离。设计的问题被显示相当于与居民区(一般为NP-硬)经过修改的3D旅行推销员问题。为了解决这一困难问题,我们提出了一种迭代算法,以高效地获得高质量的次优化无人驾驶飞行器的3D图像摄像路点及其对 GTs的访问顺序。数字结果显示,与各种基准计划相比,拟议的算法大大降低了无人驾驶飞行器的旅行距离,同时满足了图像解像要求。