In this paper, we address the problem of autonomous search and vessel detection in an unknown GNSS-denied maritime environment with fixed-wing UAVs. The main challenge in such environments with limited localization, communication range, and the total number of UAVs and sensors is to implement an appropriate search strategy so that a target vessel can be detected as soon as possible. Thus we present informed and non-informed methods used to search the environment. The informed method relies on an obtained probabilistic map, while the non-informed method navigates the UAVs along predefined paths computed with respect to the environment. The vessel detection method is trained on synthetic data collected in the simulator with data annotation tools. Comparative experiments in simulation have shown that our combination of sensors, search methods and a vessel detection algorithm leads to a successful search for the target vessel in such challenging environments.

翻译：本文研究了在未知且全球导航卫星系统（GNSS）拒止的海洋环境中，利用固定翼无人机进行自主搜索与船只检测的问题。在此类定位受限、通信距离有限、且无人机及传感器总数受限的环境中，主要挑战在于实施合适的搜索策略，以便尽快检测到目标船只。为此，我们提出了基于信息引导和非信息引导的两种环境搜索方法。信息引导方法依赖于获得的概率地图，而非信息引导方法则引导无人机沿根据环境预定义的路径航行。船只检测方法基于模拟器中带数据标注工具采集的合成数据进行训练。仿真对比实验表明，我们的传感器组合、搜索方法以及船只检测算法能够在此类具有挑战性的环境中成功搜索到目标船只。