{"title":"阵列处理中的噪声协方差建模","authors":"B. Friedlander, A. Weiss","doi":"10.1109/SSAP.1994.572467","DOIUrl":null,"url":null,"abstract":"We consider the problem of direction finding in the presence of colored noise whose covariance matrix is unknown. The ambient noise covariance matrix can be modeled by a sum of Hermitian matrices known up to a multiplicative scalar. Using this model, we estimate jointly the directions of arrival of the signals and the noise model parameters. Under certain conditions, it is possible to obtain unbiased and efficient estimates of the signal directions.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Noise Covariance Modeling In Array Processing\",\"authors\":\"B. Friedlander, A. Weiss\",\"doi\":\"10.1109/SSAP.1994.572467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of direction finding in the presence of colored noise whose covariance matrix is unknown. The ambient noise covariance matrix can be modeled by a sum of Hermitian matrices known up to a multiplicative scalar. Using this model, we estimate jointly the directions of arrival of the signals and the noise model parameters. Under certain conditions, it is possible to obtain unbiased and efficient estimates of the signal directions.\",\"PeriodicalId\":151571,\"journal\":{\"name\":\"IEEE Seventh SP Workshop on Statistical Signal and Array Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Seventh SP Workshop on Statistical Signal and Array Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSAP.1994.572467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1994.572467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We consider the problem of direction finding in the presence of colored noise whose covariance matrix is unknown. The ambient noise covariance matrix can be modeled by a sum of Hermitian matrices known up to a multiplicative scalar. Using this model, we estimate jointly the directions of arrival of the signals and the noise model parameters. Under certain conditions, it is possible to obtain unbiased and efficient estimates of the signal directions.
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