{"title":"基于最优传感器切换的数据融合","authors":"E. Skafidas, R. Evans, A. Logothetis","doi":"10.1109/ADFS.1996.581091","DOIUrl":null,"url":null,"abstract":"In this paper we consider the problem of selecting the optimal measurement sequence from two or more sensors given communication bandwidth limitations. In particular the constraints are such that only one sensor may be used at any one time. Our aim is to switch these sensors to obtain optimal (mean square error sense) estimates of the state of a linear continuous time Gauss-Markov system.","PeriodicalId":254509,"journal":{"name":"Proceeding of 1st Australian Data Fusion Symposium","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Data fusion by optimal sensor switching\",\"authors\":\"E. Skafidas, R. Evans, A. Logothetis\",\"doi\":\"10.1109/ADFS.1996.581091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we consider the problem of selecting the optimal measurement sequence from two or more sensors given communication bandwidth limitations. In particular the constraints are such that only one sensor may be used at any one time. Our aim is to switch these sensors to obtain optimal (mean square error sense) estimates of the state of a linear continuous time Gauss-Markov system.\",\"PeriodicalId\":254509,\"journal\":{\"name\":\"Proceeding of 1st Australian Data Fusion Symposium\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceeding of 1st Australian Data Fusion Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ADFS.1996.581091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceeding of 1st Australian Data Fusion Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ADFS.1996.581091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we consider the problem of selecting the optimal measurement sequence from two or more sensors given communication bandwidth limitations. In particular the constraints are such that only one sensor may be used at any one time. Our aim is to switch these sensors to obtain optimal (mean square error sense) estimates of the state of a linear continuous time Gauss-Markov system.
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