基于CM-CFAR参数学习的异物碎片雷达平方律检测器

Kudret Akcapinar, S. Baykut
{"title":"基于CM-CFAR参数学习的异物碎片雷达平方律检测器","authors":"Kudret Akcapinar, S. Baykut","doi":"10.23919/eumc.2018.8541714","DOIUrl":null,"url":null,"abstract":"One of the main challenges in foreign object debris detection radar systems is the statistical characterization of the received signals. In this paper, Non-Central Chi-square Distribution with Unequal Variances is proposed to characterize the received background signal. A practical search algorithm for the determination of the detection threshold under this distribution is also suggested. Through both Monte Carlo simulations and real data measurements, the comparison of the proposed detection procedure with widely used statistical models is made in terms of fulfillment of the given false alarm probability.","PeriodicalId":171460,"journal":{"name":"2018 15th European Radar Conference (EuRAD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CM-CFAR Parameter Learning Based Square-Law Detector For Foreign Object Debris Radar\",\"authors\":\"Kudret Akcapinar, S. Baykut\",\"doi\":\"10.23919/eumc.2018.8541714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the main challenges in foreign object debris detection radar systems is the statistical characterization of the received signals. In this paper, Non-Central Chi-square Distribution with Unequal Variances is proposed to characterize the received background signal. A practical search algorithm for the determination of the detection threshold under this distribution is also suggested. Through both Monte Carlo simulations and real data measurements, the comparison of the proposed detection procedure with widely used statistical models is made in terms of fulfillment of the given false alarm probability.\",\"PeriodicalId\":171460,\"journal\":{\"name\":\"2018 15th European Radar Conference (EuRAD)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th European Radar Conference (EuRAD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/eumc.2018.8541714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th European Radar Conference (EuRAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/eumc.2018.8541714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

异物碎片探测雷达系统面临的主要挑战之一是接收信号的统计特性。本文提出了一种方差不等的非中心卡方分布来表征接收到的背景信号。提出了一种实用的搜索算法来确定这种分布下的检测阈值。通过蒙特卡罗模拟和实际数据测量,将所提出的检测方法与广泛使用的统计模型在满足给定虚警概率方面进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CM-CFAR Parameter Learning Based Square-Law Detector For Foreign Object Debris Radar
One of the main challenges in foreign object debris detection radar systems is the statistical characterization of the received signals. In this paper, Non-Central Chi-square Distribution with Unequal Variances is proposed to characterize the received background signal. A practical search algorithm for the determination of the detection threshold under this distribution is also suggested. Through both Monte Carlo simulations and real data measurements, the comparison of the proposed detection procedure with widely used statistical models is made in terms of fulfillment of the given 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
×
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:604180095
Book学术官方微信