利用专家推理提高GLRT的性能

M. Wicks
{"title":"利用专家推理提高GLRT的性能","authors":"M. Wicks","doi":"10.1109/NAECON.2017.8268791","DOIUrl":null,"url":null,"abstract":"This paper presents the use of tailored covariance matrix estimates that may differ for the three components of the GLRT. These components are an adaptive filter and two different quadratic forms that function as a limiter and a detector. Expert reasoning is used to optimize the covariance matrix in each component.","PeriodicalId":306091,"journal":{"name":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the use of expert reasoning to enhance GLRT performance\",\"authors\":\"M. Wicks\",\"doi\":\"10.1109/NAECON.2017.8268791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the use of tailored covariance matrix estimates that may differ for the three components of the GLRT. These components are an adaptive filter and two different quadratic forms that function as a limiter and a detector. Expert reasoning is used to optimize the covariance matrix in each component.\",\"PeriodicalId\":306091,\"journal\":{\"name\":\"2017 IEEE National Aerospace and Electronics Conference (NAECON)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE National Aerospace and Electronics Conference (NAECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAECON.2017.8268791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE National Aerospace and Electronics Conference (NAECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.2017.8268791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文介绍了定制的协方差矩阵估计的使用,这可能不同于GLRT的三个组成部分。这些组件是一个自适应滤波器和两个不同的二次型,作为限制器和检测器。采用专家推理对各分量的协方差矩阵进行优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the use of expert reasoning to enhance GLRT performance
This paper presents the use of tailored covariance matrix estimates that may differ for the three components of the GLRT. These components are an adaptive filter and two different quadratic forms that function as a limiter and a detector. Expert reasoning is used to optimize the covariance matrix in each component.
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:481959085
Book学术官方微信