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Proactive Eavesdropping via Jamming for Trajectory Tracking of UAVs

机译:通过干扰主动侦听无人机轨迹

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This paper considers that a legitimate UAV tracks suspicious UAVs' flight for preventing intended crimes and terror attacks. To enhance tracking accuracy, the legitimate UAV proactively eavesdrops suspicious UAVs' communication via sending jamming signals. A tracking algorithm is developed for the legitimate UAV to track the suspicious flight by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter's signal. A new co-simulation framework is implemented to combine the complementary features of optimization toolbox with channel modeling (in Matlab) and discrete event-driven mobility tracking (in NS3). Moreover, numerical results validate the proposed algorithms in terms of tracking accuracy of the suspicious UAVs' trajectory.
机译:本文认为,合法的无人机会追踪可疑的无人机,以防止故意犯罪和恐怖袭击。为了提高跟踪精度,合法的无人机通过发送干扰信号来主动窃听可疑无人机的通信。通过全面利用窃听数据包,到达角度和可疑发射机信号的接收信号强度,为合法无人机开发了一种跟踪算法,以跟踪可疑飞行。实施了新的联合仿真框架,以将优化工具箱的互补功能与通道建模(在Matlab中)和离散事件驱动的移动性跟踪(在NS3中)相结合。此外,数值结果在可疑无人机轨迹的跟踪精度方面验证了所提出的算法。

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