Using wavelet packets to analyze FM LPI radar signals

Sergio R. Neves, Aline de Oliveira, Rafael Serra, Luiz Eugenio Segadilha, Fatima Monteiro, Jean-Marc Lopez
{"title":"Using wavelet packets to analyze FM LPI radar signals","authors":"Sergio R. Neves, Aline de Oliveira, Rafael Serra, Luiz Eugenio Segadilha, Fatima Monteiro, Jean-Marc Lopez","doi":"10.1109/SAM.2016.7569703","DOIUrl":null,"url":null,"abstract":"The FM (Frequency Modulated) LPI (Low Probability of Intercept) radars, unlike conventional radars, transmit a long or a continuous signal, with low power, using causal modulation. These LPI radar characteristics make it virtually invisible to conventional RWRs (Radar Warning Receivers) and ESM (Electronic Support Measures) receivers. Many studies in the EW (Electronic Warfare) field are being carried out to deal with this LPI radar advantage. One promising approach is the employment by ESM equipments of time-frequency transform methods to find causality in the spectrum's noise. This paper applies the WPT (Wavelet Packets Transform) to the matter of generating a portrait of the electromagnetic spectrum, aiming the milestone for an automatic classification method. We compare the time-frequency portrait of FM LPI radar signals obtained through the WPT and the well-known Choi-Williams and Fourier transforms. Results obtained from real data show some advantages to the WPT.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"50 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2016.7569703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

The FM (Frequency Modulated) LPI (Low Probability of Intercept) radars, unlike conventional radars, transmit a long or a continuous signal, with low power, using causal modulation. These LPI radar characteristics make it virtually invisible to conventional RWRs (Radar Warning Receivers) and ESM (Electronic Support Measures) receivers. Many studies in the EW (Electronic Warfare) field are being carried out to deal with this LPI radar advantage. One promising approach is the employment by ESM equipments of time-frequency transform methods to find causality in the spectrum's noise. This paper applies the WPT (Wavelet Packets Transform) to the matter of generating a portrait of the electromagnetic spectrum, aiming the milestone for an automatic classification method. We compare the time-frequency portrait of FM LPI radar signals obtained through the WPT and the well-known Choi-Williams and Fourier transforms. Results obtained from real data show some advantages to the WPT.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用小波包分析调频LPI雷达信号
与传统雷达不同,调频LPI(低截获概率)雷达采用因果调制,以低功率传输长信号或连续信号。LPI雷达的这些特性使得传统的RWRs(雷达警告接收器)和ESM(电子支持措施)接收器几乎看不见它。为了应对LPI雷达的这种优势,正在进行电子战领域的许多研究。一种很有前途的方法是利用ESM设备的时频变换方法来发现频谱噪声中的因果关系。本文将小波包变换应用于电磁波谱图像的生成,为自动分类方法的发展奠定了基础。我们比较了通过WPT和著名的Choi-Williams和傅里叶变换获得的FM LPI雷达信号的时频肖像。实测数据表明,该方法具有一定的优越性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation Performance improvement for wideband DOA estimation with white noise reduction based on uniform linear arrays Hardware design and optimal ADC resolution for uplink massive MIMO systems Point and beam-sparse radio astronomical source recovery using non-negative least squares Privacy preserving decentralized power system state estimation with phasor measurement units
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1