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空天防御  2025, Vol. 8 Issue (1): 10-16    
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  无人机协同与对抗技术 本期目录 | 过刊浏览 | 高级检索 |
基于微多普勒信号的无人机回波检测技术研究
闫军1, 顾村锋2, 孔德永3, 龚江昆1
1. 武汉大学 测绘遥感信息工程全国重点实验室,湖北 武汉 430079; 2. 上海机电工程研究所,上海 201109; 3. 湖北经济学院,湖北 武汉 430205
Research on Radar Detection of Drones Using Micro-Doppler Signals
YAN Jun1, GU Cunfeng2, KONG Deyong3, GONG Jiangkun1
1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, Hubei, China; 2. Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China; 3. Hubei University of Economics, Wuhan 430205, Hubei, China
全文: PDF(889 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 近年来,随着无人机的广泛应用,反无人机雷达技术得到了迅猛发展。然而,由于常见无人机具有体积小、雷达散射面积(RCS)有限、运动速度较慢等特点,其雷达回波往往被强烈的背景杂波淹没。传统的基于回波信噪比(SNR)的检测方法存在漏警率高和探测距离短的问题。为此,本文提出了一种创新的检测方法:通过分析无人机旋翼产生的微多普勒信号,即旋翼调制(JEM)效应对应的微多普勒信号,设计了基于回波信杂比(SCR)的检测技术,以实现对目标回波的相对检测。通过微波暗室和雷达外场实验,发现四旋翼无人机和垂直起降无人机在多个雷达测试波段均显著产生微多普勒信号。对比实验结果表明,在海杂波环境下,SCR检测相较于SNR检测具有更好的稳定性、更高的检测效率以及更低的漏警率。
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关键词 反无人机雷达无人机探测漏警率微多普勒旋翼调制信杂比    
Abstract:Recently, the proliferation of drones has driven significant advancements in anti-drone radar systems. However, radar signals produced by the small radar cross-sections (RCS) and low velocities of drones is challenging to detect, especially when obscured by background clutter. This leads to high missed alarm rates and limited detection ranges when using traditional signal-to-noise ratio (SNR) detectors. In this paper, a method transforming the micro-Doppler signals from drones into jet engine modulation (JEM) Doppler signals was proposed. Then, a signal-to-clutter ratio (SCR) detector specifically designed to identify these Doppler signals was introduced. Test results from both a microwave anechoic chamber and outdoor environments demonstrate that micro-Doppler signals are captured in the radar echoes of both quad-rotor and VTOL fixed-wing drones across multiple radar bands. Besides, the SCR detector outperforms the SNR detector, exhibiting better detection stability, higher detection probabilities, and lower missed alarm rates.
Key wordsanti-drone radar system    drone detection    missed alarm    micro-Doppler    jet engine modulation (JEM)    signal-to-clutter ratio (SCR)
收稿日期: 2023-05-10      出版日期: 2025-03-22
ZTFLH:  V 279  
  TN 959.1+7  
基金资助:湖北省自然科学基金资助项目(2023AFB130); 2024年度科技智库青年人才计划(XMSB20240710063);中国航天科技集团有限公司上海航天科技创新基金资助项目(SAST2018-007)
作者简介: 闫军(1974—),男,博士,教授。
引用本文:   
闫军, 顾村锋, 孔德永, 龚江昆. 基于微多普勒信号的无人机回波检测技术研究[J]. 空天防御, 2025, 8(1): 10-16.
YAN Jun, GU Cunfeng, KONG Deyong, GONG Jiangkun. Research on Radar Detection of Drones Using Micro-Doppler Signals. Air & Space Defense, 2025, 8(1): 10-16.
链接本文:  
https://www.qk.sjtu.edu.cn/ktfy/CN/      或      https://www.qk.sjtu.edu.cn/ktfy/CN/Y2025/V8/I1/10

参考文献
[1] 李楚晨, 唐善军, 赵冰青. 一种基于无人机探测图像区块信息的弱小目标检测算法[J]. 空天防御, 2025, 8(1): 41-47.
[2] 王冠阳, 李晨, 于英杰, 邓晓波, 芦达, 梁军利, 汪涛. 基于微多普勒特征的直升机目标识别[J]. 空天防御, 2024, 7(2): 63-73.
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