{"title":"随机振幅和相位确定的多分量信号的参数估计","authors":"J.M. Frances, B. Friedlander","doi":"10.1109/SSAP.1994.572420","DOIUrl":null,"url":null,"abstract":"We consider a class of nonstationary multi component signals, where each component has a random amplitude and a deterministic phase. The amplitude is a stationary Gaussian process plus a time varying mean. The phase and the amplitude mean are characterized by linear parametric models, while the covariance of the amplitude function is parameterized in some general manner. This model encompasses signals which are commonly used in communications, radar, sonar, and other engineering systems. We derive the Cramer Rao Bound for the estimates of the amplitude and phase parameters.","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":"2","resultStr":"{\"title\":\"Parametric Estimation Of Multi-component Signals With Random Amplitude And Deterministic Phase\",\"authors\":\"J.M. Frances, B. Friedlander\",\"doi\":\"10.1109/SSAP.1994.572420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider a class of nonstationary multi component signals, where each component has a random amplitude and a deterministic phase. The amplitude is a stationary Gaussian process plus a time varying mean. The phase and the amplitude mean are characterized by linear parametric models, while the covariance of the amplitude function is parameterized in some general manner. This model encompasses signals which are commonly used in communications, radar, sonar, and other engineering systems. We derive the Cramer Rao Bound for the estimates of the amplitude and phase parameters.\",\"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\":\"2\",\"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.1994.572420\",\"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.1994.572420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parametric Estimation Of Multi-component Signals With Random Amplitude And Deterministic Phase
We consider a class of nonstationary multi component signals, where each component has a random amplitude and a deterministic phase. The amplitude is a stationary Gaussian process plus a time varying mean. The phase and the amplitude mean are characterized by linear parametric models, while the covariance of the amplitude function is parameterized in some general manner. This model encompasses signals which are commonly used in communications, radar, sonar, and other engineering systems. We derive the Cramer Rao Bound for the estimates of the amplitude and phase parameters.