摘要: |
为了降低无人机微多普勒特征信号检测难度,提出了一种基于无源雷达与循环谱相结合的微多普勒特征检测算法。首先,建立基于数字电视地面广播(Digital Terrestrial Multimedia Broadcast,DTMB)的无源雷达回波信号模型,分析各成分信号的循环谱,并提取循环谱的等高图获得二维特征信息;然后,将无人机旋翼对DTMB信号的微动调制作为检测目标,在此基础上进行循环谱检测和理论仿真。该算法在不进行复杂的杂波抑制的前提下直接对接收信号做循环平稳处理,实测结果验证了该算法能较准确地检测到无人机的微多普勒特征。 |
关键词: 无人机 无源雷达 微多普勒特征 数字电视地面广播(DTMB) 循环平稳特性 循环谱 |
DOI: |
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基金项目:国家自然科学基金资助项目(6146105);广西科技重大专项资助项目(AA17202022);广西高校中青年教师科研基础能力提升项目(2019KY1035);桂林电子科技大学研究生教育创新计划项目(2020YCXS021) |
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Micro-motion feature detection of UAV based on passive radar and cyclic spectrum |
XIE Yuelei,LIU Xin,LIANG Wenbin |
(a.School of Information and Communication;b.Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing,Guilin University of Electronic Technology,Guilin 541004,China;School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China;School of Information Technology,Guilin University of Electronic Technology,Guilin 541004,China) |
Abstract: |
In order to reduce the difficulty of unmanned aerial vehicle(UAV) micro-Doppler characteristic signal detection,a micro-Doppler feature detection algorithm based on passive radar and cyclic spectrum is proposed.Firstly,a passive radar echo signal model based on digital TV terrestrial broadcasting digital terrestrial multimedia broadcast(DTMB) is established,the cyclic spectrum of each component signal is analyzed,and the contour map of the cyclic spectrum is extracted to obtain two-dimensional feature information.Then,the micro-motion modulation of the DTMB signal by the UAV rotor is used as the detection target,and on this basis,the cyclic spectrum detection and theoretical simulation are performed.The algorithm directly performs cyclic processing on the received signal without complex clutter suppression.The experimental results verify that the algorithm can accurately detect the micro-Doppler characteristics of the UAV. |
Key words: unmanned aerial vehicle passive radar micro-Doppler characteristics digital terrestrial multimedia broadcast(DTMB) cyclostationary characteristics cyclic spectrum |