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同频段混合信号中的无人机信号盲检测识别 被引量:3

Blind Detection and Recognition of UAV Signal in Mixed Signal in Same Frequency Band
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摘要 无人机信号的探测识别技术是应对无人机黑飞滥用的关键技术之一。在实际信号监测环境中,经常会接收到多个信号的混合信号,它们在时域和频域上混叠且各信号分量调制样式相同。为解决在同频段混合信号中检测识别出无人机信号的问题,提出了一种通过谱特征分析判断无人机信号存在性的方法。分别采用基于二次方谱特征的无人机图传和WiFi混合信号检测识别算法以及基于频谱带宽特征的多无人机混合信号检测识别算法,通过对射频电路采集的信号进行仿真验证,实现了从同频段混合信号中检测识别出无人机信号分量。理论分析和实验测试结果证实了所提检测识别算法的有效性。 The technology of detection and identification of unmanned aerial vehicle(UAV)signal is one of the key technologies to deal with the abuse and illegally-flying of UAV.In an actual signal monitoring environment,mixed signal of multiple signals is often received,the time domain and the frequency domain of these signal components are overlapped with the same modulation pattern.In order to solve the problem of detecting and identifying the UAV signals from the received mixed signal in the same frequency band,a technique for judging the existence of the UAV signals by analyzing the spectrum characteristics is proposed.The detection and recognition algorithm of a UAV and WiFi mixed signal based on square spectrum characteristics and the recognition algorithm of a multi-UAV mixed signal based on spectral bandwidth characteristics are adopted respectively.Through the simulation and verification of the signals collected by the radio frequency(RF)circuit,the detection and recognition of UAV signal component from a mixed signal in the same frequency band is realized.Theoretical analysis and experimental results demonstrate that the proposed algorithms is effective.
作者 曾政智 周嘉伟 罗正华 ZENG Zhengzhi;ZHOU Jiawei;LUO Zhenghua(The Fifth Research Institute of Telecommunications Science and Technology,Chengdu 610021,China;School of Information Science and Engineering,Chengdu University,Chengdu 610106,China)
出处 《电讯技术》 北大核心 2020年第6期689-694,共6页 Telecommunication Engineering
基金 四川省科技计划项目(2018GZ0072,2018GZ0509) 四川省科技计划省院省校合作项目(2018JZ0065)。
关键词 无人机信号 探测识别 混合信号 时频混叠 谱特征 unmanned aerial vehicle(UAV)signal detection and recognition mixed signal time-frequency overlapped spectrum characteristics
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