{"title":"基于协方差矩阵非线性函数的频谱估计频率分辨率研究","authors":"Jun Chen, Yewei Wu, An Li","doi":"10.1109/ICOSP.2012.6491646","DOIUrl":null,"url":null,"abstract":"This paper studies the frequency resolution of two existing spectral estimators, where one is a generalization of the minimum variance spectral estimators (GMVSE) and the other is Pisarenko's non-linear spectral estimators (PNLSE). By this study, we show the uncovered relationship between the non-linear parameter and the frequency resolution for both the GMVSE and the PNLSE. The results bring out a clear guideline on choosing the parameters for both the GMVSE and the PNLSE to avoid missing any sinusoids.","PeriodicalId":143331,"journal":{"name":"2012 IEEE 11th International Conference on Signal Processing","volume":"279 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on frequency resolution of spectral estimators using non-linear functions of the covariance matrix\",\"authors\":\"Jun Chen, Yewei Wu, An Li\",\"doi\":\"10.1109/ICOSP.2012.6491646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the frequency resolution of two existing spectral estimators, where one is a generalization of the minimum variance spectral estimators (GMVSE) and the other is Pisarenko's non-linear spectral estimators (PNLSE). By this study, we show the uncovered relationship between the non-linear parameter and the frequency resolution for both the GMVSE and the PNLSE. The results bring out a clear guideline on choosing the parameters for both the GMVSE and the PNLSE to avoid missing any sinusoids.\",\"PeriodicalId\":143331,\"journal\":{\"name\":\"2012 IEEE 11th International Conference on Signal Processing\",\"volume\":\"279 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 11th International Conference on Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2012.6491646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 11th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2012.6491646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on frequency resolution of spectral estimators using non-linear functions of the covariance matrix
This paper studies the frequency resolution of two existing spectral estimators, where one is a generalization of the minimum variance spectral estimators (GMVSE) and the other is Pisarenko's non-linear spectral estimators (PNLSE). By this study, we show the uncovered relationship between the non-linear parameter and the frequency resolution for both the GMVSE and the PNLSE. The results bring out a clear guideline on choosing the parameters for both the GMVSE and the PNLSE to avoid missing any sinusoids.
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