Performance of global navigation satellite systems (GNSSs) mounted on aerial platforms could be degraded by the presence of jamming or spoofing threats. Detection of jamming and spoofing is essential considering practical applications of satellite navigation in passenger aircrafts, unmanned aerial vehicles (UAVs), helicopters and fighters. Different algorithms and methods have been proposed for detection of these threats; however, their usage has many limitations because of their demanding weight, size and computational complexity, when embedded on aerial systems. In this study, the authors develop a theoretical framework to detect the presence of the threat of UAVs. The idea is based on the fact that, due to the UAV motion, the samples of received signal power from a fixed threat and from a GNSS satellite have different empirical probability density functions. Moreover, by using two antennas (an omnidirectional and a down-tilted-directional), they introduce a new method to distinguish between aerial and ground-based threats. The proposed algorithms have a low-computational burden and can consider the fading loss as well. Simulation results show the superior performance of the proposed methods, in terms of detection and false alarm probability, compared to the existing methods.

中文翻译：

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用于移动平台上GNSS干扰和欺骗检测的低复杂度框架

由于存在干扰或欺骗威胁，安装在空中平台上的全球导航卫星系统（GNSS）的性能可能会降低。考虑到卫星导航在客机，无人飞行器（UAV），直升机和战斗机中的实际应用，检测干扰和欺骗至关重要。已经提出了用于检测这些威胁的不同算法和方法。然而，由于它们的要求重量，尺寸和计算复杂性，当将它们嵌入空中系统时，它们的使用受到许多限制。在这项研究中，作者开发了一种理论框架来检测无人机威胁的存在。这个想法基于以下事实：由于无人机的运动，来自固定威胁和GNSS卫星的接收信号功率样本具有不同的经验概率密度函数。此外，通过使用两个天线（全向和向下倾斜的天线），他们引入了一种新的方法来区分空中和地面威胁。所提出的算法具有低计算负担并且也可以考虑衰落损耗。仿真结果表明，与现有方法相比，该方法在检测和误报几率方面具有优越的性能。