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Micro-UAV Detection with a Low-Grazing Angle Millimeter Wave Radar

机译:低掠角毫米波雷达的微型无人机检测

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Millimeter wave radars are popularly used in last-mile radar-based defense systems. Detection of low-altitude airborne target using these radars at low-grazing angles is an important problem in the field of electronic warfare, which becomes challenging due to the significant effects of clutters in the terrain. This paper provides both experimental and analytical investigation of micro unmanned aerial vehicle (UAV) detection in a rocky terrain using a low grazing angle, surface-sited 24 GHz dual polarized frequency modulated continuous wave (FMCW) radar. The radar backscatter signal from the UAV is polluted by land clutters which is modeled using a uniform Weibull distribution. A constant false alarm rate (CFAR) detector which employs adaptive thresholding is designed to detect the UAV in the rich clutter background. In order to further enhance the discrimination of the UAV from the clutter, the micro-Doppler signature of the rotating propellers and bulk trajectory of the UAV are extracted and plotted in the time-frequency domain.
机译:毫米波雷达广泛用于基于最后一英里雷达的防御系统。使用这些雷达以低掠角检测低空机载目标是电子战领域的一个重要问题,由于地形杂波的巨大影响,这变得具有挑战性。本文提供了使用低掠角,表面定位的24 GHz双极化频率调制连续波(FMCW)雷达在岩石地形中检测微型无人机(UAV)的实验和分析研究。来自无人机的雷达反向散射信号受到陆地杂波的污染,该杂波使用统一的威布尔分布进行建模。设计了采用自适应阈值的恒定虚警率(CFAR)检测器,以检测杂波背景下的无人机。为了进一步增强无人机对杂波的识别能力,提取了旋转螺旋桨的微多普勒信号和无人机的总体轨迹,并将其绘制在时频域中。

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