UAV Micro-Doppler Signature Analysis Using DVB-S Based Passive Radar

M. Ummenhofer, Louis Cesbron Lavau, D. Cristallini, D. O’Hagan
{"title":"UAV Micro-Doppler Signature Analysis Using DVB-S Based Passive Radar","authors":"M. Ummenhofer, Louis Cesbron Lavau, D. Cristallini, D. O’Hagan","doi":"10.1109/RADAR42522.2020.9114747","DOIUrl":null,"url":null,"abstract":"Drones and unmanned aerial vehicles (UAVs) are increasingly popular, thus posing danger and threats to infrastructures and public safety. A technology for drone detection and classification would therefore significantly increase the level of security. In scenarios such as concerts, sport events, trade fairs, or in any situation where significant aggregation of people is present, such techniques should be non-invasive. That means they do not have to pose an additional threat to people themselves. To this end, passive radars offer an appealing solution, since they are able to offer a non-cooperative surveillance while not emitting any electromagnetic signal. On the contrary, they rely on existing transmitting infrastructure (also referred to as illuminators of opportunity, IoO), such as broadcasting signal sources (FM radio, terrestrial and satellite digital video broadcasting, cellular communication and so on). In this work, the possibility to exploit satellite television based passive radar for UAV detection is analyzed by experimental validation. In addition, micro-Doppler signatures for drones have been extracted, which might give information for subsequent UAV classification.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Radar Conference (RADAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR42522.2020.9114747","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

Drones and unmanned aerial vehicles (UAVs) are increasingly popular, thus posing danger and threats to infrastructures and public safety. A technology for drone detection and classification would therefore significantly increase the level of security. In scenarios such as concerts, sport events, trade fairs, or in any situation where significant aggregation of people is present, such techniques should be non-invasive. That means they do not have to pose an additional threat to people themselves. To this end, passive radars offer an appealing solution, since they are able to offer a non-cooperative surveillance while not emitting any electromagnetic signal. On the contrary, they rely on existing transmitting infrastructure (also referred to as illuminators of opportunity, IoO), such as broadcasting signal sources (FM radio, terrestrial and satellite digital video broadcasting, cellular communication and so on). In this work, the possibility to exploit satellite television based passive radar for UAV detection is analyzed by experimental validation. In addition, micro-Doppler signatures for drones have been extracted, which might give information for subsequent UAV classification.
基于DVB-S无源雷达的无人机微多普勒特征分析
无人机和无人驾驶飞行器日益普及,给基础设施和公共安全带来了危险和威胁。因此,无人机探测和分类技术将大大提高安全水平。在音乐会、体育赛事、交易会等场景中,或在任何有大量人员聚集的情况下,此类技术应该是非侵入性的。这意味着他们不必对人们本身构成额外的威胁。为此,无源雷达提供了一个有吸引力的解决方案,因为它们能够在不发射任何电磁信号的情况下提供非合作监视。相反,它们依赖于现有的传输基础设施(也称为机会照明器,IoO),例如广播信号源(调频无线电、地面和卫星数字视频广播、蜂窝通信等)。通过实验验证,分析了利用卫星电视无源雷达进行无人机探测的可能性。此外,还提取了无人机的微多普勒特征,为后续的无人机分类提供了信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信