{"title":"在存在信号的情况下自动进行本底噪声频谱估计","authors":"M. Ready, M. Downey, Leo J. Corbalis","doi":"10.1109/ACSSC.1997.680569","DOIUrl":null,"url":null,"abstract":"This paper describes a technique for automatically estimating the noise floor spectrum in the presence of signals. The technique works equally well for both flat and non-flat noise floor spectra. The technique is based on applying morphological binary image processing operators to a binary image of the received power spectrum. It is related to rank-order filters but is more computationally efficient. The performance is illustrated on the detection of radio signals.","PeriodicalId":240431,"journal":{"name":"Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"Automatic noise floor spectrum estimation in the presence of signals\",\"authors\":\"M. Ready, M. Downey, Leo J. Corbalis\",\"doi\":\"10.1109/ACSSC.1997.680569\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a technique for automatically estimating the noise floor spectrum in the presence of signals. The technique works equally well for both flat and non-flat noise floor spectra. The technique is based on applying morphological binary image processing operators to a binary image of the received power spectrum. It is related to rank-order filters but is more computationally efficient. The performance is illustrated on the detection of radio signals.\",\"PeriodicalId\":240431,\"journal\":{\"name\":\"Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)\",\"volume\":\"133 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.1997.680569\",\"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 the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.1997.680569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic noise floor spectrum estimation in the presence of signals
This paper describes a technique for automatically estimating the noise floor spectrum in the presence of signals. The technique works equally well for both flat and non-flat noise floor spectra. The technique is based on applying morphological binary image processing operators to a binary image of the received power spectrum. It is related to rank-order filters but is more computationally efficient. The performance is illustrated on the detection of radio signals.