The authors deal with the problem of the design and manufacture of a high-resolution FMCW radar for drone detection and classification. The difficulties of the problem are discrete clutter reduction and spurious phase noise mitigation. The discrete clutter is due to the reflected signals from land vehicles, birds etc., while the spurious phase noise is inherent in the radar signal due to the phase-locked loop component and leakage between the transmitting and receiving paths. Both spurious phase noise and clutter will increase the system noise level and hence reduce the probability of detection of small targets such as drones and induce false alarms on the radar screen. In order to reduce discrete clutter, the authors propose a method to separate a drone from discrete clutter based on the design of the radar system parameters for a drone and its propeller detection, target's Doppler dispersion and moving characteristics. For spur mitigation, a method that focuses on the design of the isolation coefficient between transmitting and receiving paths to decrease the power of spurs below the minimum power requirement at the input of the analogue-to-digital converter is introduced. The results were applied by the authors to the development and manufacture of a radar with the given specifications for drone detection and classification. Different laboratory and field tests show that the spurs are mitigated and the drones are separated from discrete clutter with a range and accuracy better than the one recently published.

中文翻译：

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基于杂散相位噪声和离散杂波抑制的无人机检测高分辨率调频连续波雷达设计

作者解决了用于无人机检测和分类的高分辨率 FMCW 雷达的设计和制造问题。该问题的难点在于减少离散杂波和减轻杂散相位噪声。离散杂波是由陆地车辆、鸟类等的反射信号引起的，而寄生相位噪声是由于锁相环组件以及发射和接收路径之间的泄漏而在雷达信号中固有的。杂散相位噪声和杂波都会增加系统噪声水平，从而降低检测无人机等小目标的概率，并在雷达屏幕上引起误报。为了减少离散杂波，作者根据无人机雷达系统参数设计及其螺旋桨检测、目标多普勒色散和运动特性，提出了一种将无人机与离散杂波分离的方法。为了抑制杂散，引入了一种方法，该方法侧重于发送和接收路径之间的隔离系数的设计，以将杂散功率降低到模数转换器输入端的最小功率要求以下。作者将研究结果应用于具有给定无人机检测和分类规范的雷达的开发和制造。不同的实验室和现场测试表明，杂波得到了缓解，无人机从离散杂波中分离出来，其范围和精度都比最近发布的更好。