| 摘要: |
| 随着无人机技术的快速发展，无人机集群在安防、战争、工业和交通等领域的应用日益频繁。然而，这些集群的广泛应用也引起了对其探测识别的深入研究。本文根据实际场景构建了微小无人机集群的窄带雷达回波信号模型，分析了旋翼无人机集群的雷达回波频域特性，结合无人机本征特性提出了一种基于微多普勒特征的识别方法。该方法通过提取无人机旋翼造成的微多普勒特征准确估计目标的转动参数，并计算旋翼长度从而识别无人机机型。通过仿真数据对所提算法的参数估计和识别性能进行了验证，结果表明了该方法的有效性和鲁棒性，得到较高的集群类型识别准确率。 |
| 关键词: 微多普勒 无人机集群 旋翼旋转 旋翼长度 |
| DOI：DOI:10.3969/j.issn.1672-2337.2025.06.011 |
| 分类号:TN957.52 |
| 基金项目:安徽省重点研发计划（No.106185490006） |
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| UAV Swarm Identification Based on Radar Micro-Doppler Features |
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ZHANG Jun, TIAN Xilan
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The 38th Research Institute of China Electronics Technology Group Corporation, Hefei 230088, China
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| Abstract: |
| Recent advancements in drone technology have led to the increased utilisation of unmanned aerial vehicle（UAV） swarms in various fields, including security, warfare, industry, and transportation. Nevertheless, the extensive utilisation of these clusters has also precipitated profound research endeavours concerning their detection and identification. In this paper, a narrowband radar echo signal model of micro-UAV swarms is constructed according to the actual scenario. The radar echo frequency domain characteristics of rotary-wing UAV swarms are analysed, and a recognition method based on micro-Doppler features is proposed based on the intrinsic characteristics of UAV. The proposed metho-dology involves the extraction of micro-Doppler features caused by the rotor of the UAV, the accurate estimation of the target’s rotation parameters, and the calculation of the rotor length to identify the UAV model. The simulation data are utilised to verify the parameter estimation and recognition performance of the proposed algorithm. The results demonstrate the effectiveness and robustness of the proposed method, and the accuracy of cluster type recognition is high. |
| Key words: micro-Doppler UAV swarms rotor rotation rotor length |
