无人机
雷达
背景(考古学)
螺旋桨
工程类
多普勒效应
计算机科学
声学
电子工程
航空航天工程
海洋工程
物理
地理
生物
考古
遗传学
天文
作者
Peter Klaer,Andi Huang,Pascale Sévigny,Sreeraman Rajan,Shashank Pant,Prakash Patnaik,Bhashyam Balaji
出处
期刊:Sensors
[MDPI AG]
日期:2020-10-21
卷期号:20 (20): 5940-5940
被引量:32
摘要
Detecting and identifying drones is of great interest due to the proliferation of highly manoeuverable drones with on-board sensors of increasing sensing capabilities. In this paper, we investigate the use of radars for tackling this problem. In particular, we focus on the problem of detecting rotary drones and distinguishing between single-propeller and multi-propeller drones using a micro-Doppler analysis. Two different radars were used, an ultra wideband (UWB) continuous wave (CW) C-band radar and an automotive frequency modulated continuous wave (FMCW) W-band radar, to collect micro-Doppler signatures of the drones. By taking a closer look at HElicopter Rotor Modulation (HERM) lines, the spool and chopping lines are identified for the first time in the context of drones to determine the number of propeller blades. Furthermore, a new multi-frequency analysis method using HERM lines is developed, which allows the detection of propeller rotation rates (spool and chopping frequencies) of single and multi-propeller drones. Therefore, the presented method is a promising technique to aid in the classification of drones.
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