基于位置尺度的FOPEN SAR图像CFAR检测框架

Marco Liguori, A. Izzo, C. Clemente, C. Galdi, M. di Bisceglie, J. Soraghan
{"title":"基于位置尺度的FOPEN SAR图像CFAR检测框架","authors":"Marco Liguori, A. Izzo, C. Clemente, C. Galdi, M. di Bisceglie, J. Soraghan","doi":"10.1109/SSPD.2015.7288497","DOIUrl":null,"url":null,"abstract":"The problem of target detection in a complex clutter environment, with Constant False Alarm Ratio (CFAR), is addressed in this paper. In particular an algorithm for CFAR target detection is applied to the context of FOliage PENetrating (FOPEN) Synthetic Aperture Radar (SAR) imaging. The extreme value distributions family is used to model the data and exploiting the location-scale property of this family of distributions, a multi-model CFAR algorithm is derived. Performance analysis on real data confirms the capability of the developed framework to control the false alarm probability.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Location Scale Based CFAR Detection Framework for FOPEN SAR Images\",\"authors\":\"Marco Liguori, A. Izzo, C. Clemente, C. Galdi, M. di Bisceglie, J. Soraghan\",\"doi\":\"10.1109/SSPD.2015.7288497\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of target detection in a complex clutter environment, with Constant False Alarm Ratio (CFAR), is addressed in this paper. In particular an algorithm for CFAR target detection is applied to the context of FOliage PENetrating (FOPEN) Synthetic Aperture Radar (SAR) imaging. The extreme value distributions family is used to model the data and exploiting the location-scale property of this family of distributions, a multi-model CFAR algorithm is derived. Performance analysis on real data confirms the capability of the developed framework to control the false alarm probability.\",\"PeriodicalId\":212668,\"journal\":{\"name\":\"2015 Sensor Signal Processing for Defence (SSPD)\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Sensor Signal Processing for Defence (SSPD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSPD.2015.7288497\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Sensor Signal Processing for Defence (SSPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSPD.2015.7288497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

研究了具有恒定虚警率的复杂杂波环境下的目标检测问题。特别提出了一种用于叶突(FOPEN)合成孔径雷达(SAR)成像的CFAR目标检测算法。利用极值分布族对数据进行建模,利用极值分布族的位置尺度特性,推导了一种多模型CFAR算法。通过对实际数据的性能分析,验证了所开发框架控制虚警概率的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Location Scale Based CFAR Detection Framework for FOPEN SAR Images
The problem of target detection in a complex clutter environment, with Constant False Alarm Ratio (CFAR), is addressed in this paper. In particular an algorithm for CFAR target detection is applied to the context of FOliage PENetrating (FOPEN) Synthetic Aperture Radar (SAR) imaging. The extreme value distributions family is used to model the data and exploiting the location-scale property of this family of distributions, a multi-model CFAR algorithm is derived. Performance analysis on real data confirms the capability of the developed framework to control the false alarm probability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Removing Speckle Noise by Analysis Dictionary Learning Extraction of Pulse Repetition Interval Based on Incomplete, Noisy TOA Measurements by the Moving Passive Receiver Traffic Scheduling Algorithm for Wireless Mesh Networks Based Defense Networks Incorporating Centralized Scheduling Architecture Direction of Arrival Estimation Using a Cluster of Beams in a Cone-Shaped Digital Array Radar Distributed Implementation for Person Re-Identification
×
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