{"title":"自适应超分辨率与MUSIC算法的比较","authors":"D. Torrieri, K. Bakhru","doi":"10.1109/MILCOM.1994.473875","DOIUrl":null,"url":null,"abstract":"Adaptive superresolution algorithms possess the inherent ability to adapt to nonstationary environments. In this paper, a representative adaptive algorithm, the recursive suppression algorithm, is shown to provide much better resolution than the MUSIC algorithm when the average signal-to-noise ratios at array outputs are low and there are power variations or there is relative motion between the array and closely spaced signal sources.<<ETX>>","PeriodicalId":337873,"journal":{"name":"Proceedings of MILCOM '94","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of adaptive superresolution with MUSIC algorithm\",\"authors\":\"D. Torrieri, K. Bakhru\",\"doi\":\"10.1109/MILCOM.1994.473875\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive superresolution algorithms possess the inherent ability to adapt to nonstationary environments. In this paper, a representative adaptive algorithm, the recursive suppression algorithm, is shown to provide much better resolution than the MUSIC algorithm when the average signal-to-noise ratios at array outputs are low and there are power variations or there is relative motion between the array and closely spaced signal sources.<<ETX>>\",\"PeriodicalId\":337873,\"journal\":{\"name\":\"Proceedings of MILCOM '94\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of MILCOM '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MILCOM.1994.473875\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of MILCOM '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MILCOM.1994.473875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of adaptive superresolution with MUSIC algorithm
Adaptive superresolution algorithms possess the inherent ability to adapt to nonstationary environments. In this paper, a representative adaptive algorithm, the recursive suppression algorithm, is shown to provide much better resolution than the MUSIC algorithm when the average signal-to-noise ratios at array outputs are low and there are power variations or there is relative motion between the array and closely spaced signal sources.<>
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