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首页> 外文期刊>The Journal of Engineering >Micro-Doppler signature for drone detection using FSR: a theoretical and experimental validation
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Micro-Doppler signature for drone detection using FSR: a theoretical and experimental validation

机译：使用FSR的无人机检测微多普勒签名：理论和实验验证

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摘要

Drone inexpensive and operational flexibility contributed to its exponential increase by civil users, apart from military applications. This resulted in posing threats due to drone misuses, such as smuggling, unlawful imaging and other significant vulnerability that makes its detection necessary. The study demonstrated a theoretical model of extracting the m-Doppler signature due to rotating blades of a quadcopter drone, in forward scattering radar (FSR) geometry. The model was further validated experimentally by using a parabolic dish antenna in the receiver system of the FSR geometry. Before these, some reported efforts made to detect the drone by using different methodologies such as acoustic, video, audio-visual, radio frequency, radar systems and other non-technical approaches like netting were briefly presented. The result of the authors' investigation revealed that the drone could be detected from the signature generated due to rotating blades based on the blade orientation. This signature can further be used to identify the drone from other flying targets existing within the same surveillance area.
机译：无人机廉价且经营的灵活性促成了民用用户的指数增加，除了军事应用。这导致由于无人机滥用而构成威胁，例如走私，非法的成像和其他具有所需检测的重要漏洞。该研究表明，由于Quadcopter无人机的旋转叶片，在前向散射雷达（FSR）几何形状中，提取M-Doppler特征的理论模型。通过在FSR几何形状的接收器系统中使用抛物线碟天线进一步通过实验验证该模型。在这些之前，一些报告的努力通过使用不同的方法来检测无人机，例如声音，视频，视听，射频，雷达系统和其他非技术方法，如网状。作者调查的结果揭示了可以根据基于叶片取向因旋转叶片而产生的签名来检测无人机。该签名可以进一步用于识别来自在同一监视区域内的其他飞行目标的无人机。

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