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Radar micro-Doppler signatures of drones and birds at K-band and W-band

机译:无人机和鸟类在K波段和W波段的雷达微多普勒信号

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摘要

Due to the substantial increase in the number of affordable drones in the consumer market and their regrettable misuse, there is a need for efficient technology to detect drones in airspace. This paper presents the characteristic radar micro-Doppler properties of drones and birds. Drones and birds both induce micro-Doppler signatures due to their propeller blade rotation and wingbeats, respectively. These distinctive signatures can then be used to differentiate a drone from a bird, along with studying them separately. Here, experimental measurements of micro-Doppler signatures of different types of drones and birds are presented and discussed. The data have been collected using two radars operating at different frequencies; K-band (24 GHz) and W-band (94 GHz). Three different models of drones and four species of birds of varying sizes have been used for data collection. The results clearly demonstrate that a phase coherent radar system can retrieve highly reliable and distinctive micro-Doppler signatures of these flying targets, both at K-band and W-band. Comparison of the signatures obtained at the two frequencies indicates that the micro-Doppler return from the W-band radar has higher SNR. However, micro-Doppler features in the K-band radar returns also reveal the micro-motion characteristics of drones and birds very effectively.
机译:由于消费市场上可负担得起的无人机数量的大量增加以及令人遗憾的滥用,因此需要一种有效的技术来检测空域中的无人机。本文介绍了无人机和鸟类的特征性雷达微多普勒特性。无人机和鸟类都分别由于螺旋桨叶片旋转和机翼搏动而引起微多普勒签名。这些独特的签名然后可以用来区分无人机和鸟类,以及分别研究它们。在这里,提出并讨论了不同类型的无人机和鸟类的微多普勒信号的实验测量。数据是使用两个工作在不同频率的雷达收集的; K波段(24 GHz)和W波段(94 GHz)。三种不同的无人机模型和四种大小不一的鸟类已用于数据收集。结果清楚地表明,相干相干雷达系统可以在K波段和W波段检索这些飞行目标的高度可靠和独特的微多普勒信号。比较在两个频率处获得的信号,表明来自W波段雷达的微多普勒回波具有更高的SNR。但是,K波段雷达回波中的微多普勒特征也非常有效地揭示了无人机和鸟类的微动特征。

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