Most of the investigations on the micro-Doppler (MD) effect caused by a small unmanned aerial vehicle (UAV) have been conducted using joint time–frequency (JTF) images rather than the Doppler spectrum. On the other hand, several researchers utilized the Doppler spectrum instead of JTF images to observe the MD signature of a small UAV, and found the relationship between the spectral distribution of a small UAV and its physical specifications. However, the studies using the Doppler spectrum still lack concrete and theoretical foundations of the MD effects of a small UAV, focusing mainly on phenomena identified by measurement data. In this article, we establish the theoretical foundation connecting the MD signatures and motion dynamics of small UAVs based on the Doppler spectrum, and analyze their spectral distribution using simulations and measured data. In addition, experimental analysis is conducted using the data measured from various types of small UAVs considering the translational motion and aspect change. In contrast to already existing investigations, we completely explain and predict the changes on the Doppler spectrum relative to the physical specifications of a small UAV (e.g., blade length and rotor rotation rate). In particular, we show that the Doppler spectrum, compared to the JTF images, is a considerably simple and useful tool for analyzing the MD effects of small flying UAVs. The analysis results reveal that the MD features obtained from the measured echoes of small UAVs have considerable potential for detection and classification of small UAVs.

中文翻译：

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基于多普勒频谱的小型无人机微多普勒特征分析


大多数关于小型无人机（UAV）引起的微多普勒（MD）效应的研究都是使用联合时频（JTF）图像而不是多普勒频谱进行的。另一方面，一些研究人员利用多普勒频谱代替JTF图像来观察小型无人机的MD特征，并发现小型无人机的频谱分布与其物理规格之间的关系。然而，利用多普勒频谱的研究仍然缺乏小型无人机MD效应的具体和理论基础，主要集中在通过测量数据识别的现象。在本文中，我们基于多普勒频谱建立了连接小型无人机的MD特征和运动动力学的理论基础，并利用仿真和测量数据分析了它们的频谱分布。此外，考虑平移运动和方位变化，利用各类小型无人机测量的数据进行实验分析。与现有的研究相比，我们完全解释和预测了多普勒频谱相对于小型无人机物理规格（例如叶片长度和旋翼转速）的变化。特别是，我们表明，与 JTF 图像相比，多普勒频谱是分析小型飞行无人机 MD 效应的相当简单且有用的工具。分析结果表明，从小型无人机实测回波中获得的MD特征对于小型无人机的检测和分类具有很大的潜力。