{"title":"主成分逆、交叉谱度量和部分自适应多级维纳滤波器的自适应检测性能","authors":"B. Freburger, D. Tufts","doi":"10.1109/ACSSC.1998.751581","DOIUrl":null,"url":null,"abstract":"This paper compares the small sample adaptive detection performance of the principal component inverse (PCI) method with the newer cross spectral metric (CSM) and partially adaptive multistage Wiener filter for the partially adaptive sidelobe canceller. By examining properties of the estimated metrics, scenarios which will result in poor performance can be identified, providing insight on the best choice of method for a given application.","PeriodicalId":393743,"journal":{"name":"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Adaptive detection performance of principal components inverse, cross spectral metric and the partially adaptive multistage Wiener filter\",\"authors\":\"B. Freburger, D. Tufts\",\"doi\":\"10.1109/ACSSC.1998.751581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper compares the small sample adaptive detection performance of the principal component inverse (PCI) method with the newer cross spectral metric (CSM) and partially adaptive multistage Wiener filter for the partially adaptive sidelobe canceller. By examining properties of the estimated metrics, scenarios which will result in poor performance can be identified, providing insight on the best choice of method for a given application.\",\"PeriodicalId\":393743,\"journal\":{\"name\":\"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.1998.751581\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.1998.751581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive detection performance of principal components inverse, cross spectral metric and the partially adaptive multistage Wiener filter
This paper compares the small sample adaptive detection performance of the principal component inverse (PCI) method with the newer cross spectral metric (CSM) and partially adaptive multistage Wiener filter for the partially adaptive sidelobe canceller. By examining properties of the estimated metrics, scenarios which will result in poor performance can be identified, providing insight on the best choice of method for a given application.