The commercial drone market has substantially grown over the past few years. While providing numerous advantages in various fields and applications, drones also provide ample opportunities for misuse by irresponsible hobbyists or malevolent actors. The increasing number of safety/security incidents in which drones are involved has motivated researchers to find new and ingenious ways to detect, locate and counter this type of vehicles. In this paper, we propose a new method to detect frequency hopping spread spectrum - Gaussian frequency-shift keying (FHSS-GFSK) drone communication signals, in a non-cooperative scenario, where no prior information about the signals of interest is available. The system is designed to detect and retrieve data bit sequences through a compressive sampling approach, which includes the extraction of the reduced spectral information and a soft detection algorithm. The performance of the proposed approach is assessed in terms of bit error rate and compared with that of a Viterbi detector and a neural network-based detector. The effectiveness of the method described in the paper highlights the fact that current UAV communications are not infallible and present real security issues.

中文翻译：

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FHSS-GFSK无人机控制信号的非合作低复杂度检测方法

在过去的几年中，商用无人机市场已经有了实质性的增长。无人机在各个领域和应用中提供众多优势的同时，还为不负责任的业余爱好者或恶意演员滥用提供了充足的机会。涉及无人机的安全/安保事件的数量不断增加，促使研究人员寻找新颖，新颖的方法来检测，定位和对付此类车辆。在本文中，我们提出了一种检测跳频扩频的新方法-高斯频移键控（FHSS-GFSK）无人机通信信号，该信号在非合作情况下无法获得有关感兴趣信号的先验信息。该系统旨在通过压缩采样方法检测和检索数据位序列，其中包括减少的光谱信息的提取和软检测算法。根据比特错误率评估了所提出方法的性能，并将其与维特比检测器和基于神经网络的检测器进行了比较。本文中描述的方法的有效性突出了这样一个事实，即当前的无人机通信不是万无一失的，并且存在真正的安全问题。