Wen-an Zhang, Steven Liu, Michael Z. Q. Chen, Li Yu
{"title":"具有非均匀估计速率的两个传感器的融合估计","authors":"Wen-an Zhang, Steven Liu, Michael Z. Q. Chen, Li Yu","doi":"10.1109/CDC.2012.6426991","DOIUrl":null,"url":null,"abstract":"The fusion estimation is investigated in this paper for two-sensor discrete-time stochastic systems. A finite-horizon optimal linear estimator is designed for each sensor to generate local estimates with a nonuniform estimation rate. Then, a fusion rule with matrix weights in the linear minimum variance sense is designed for each sensor to fuse local estimates from itself and the other sensors. The proposed algorithm reduces to the one that can be used to design asynchronous fusion estimators with uncorrelated measurement noises. Finally, the effectiveness of the proposed results is illustrated by a simulation example of a maneuvering target tracking system.","PeriodicalId":312426,"journal":{"name":"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fusion estimation for two sensors with nonuniform estimation rates\",\"authors\":\"Wen-an Zhang, Steven Liu, Michael Z. Q. Chen, Li Yu\",\"doi\":\"10.1109/CDC.2012.6426991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The fusion estimation is investigated in this paper for two-sensor discrete-time stochastic systems. A finite-horizon optimal linear estimator is designed for each sensor to generate local estimates with a nonuniform estimation rate. Then, a fusion rule with matrix weights in the linear minimum variance sense is designed for each sensor to fuse local estimates from itself and the other sensors. The proposed algorithm reduces to the one that can be used to design asynchronous fusion estimators with uncorrelated measurement noises. Finally, the effectiveness of the proposed results is illustrated by a simulation example of a maneuvering target tracking system.\",\"PeriodicalId\":312426,\"journal\":{\"name\":\"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 51st IEEE Conference on Decision and Control (CDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2012.6426991\",\"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 51st IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2012.6426991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fusion estimation for two sensors with nonuniform estimation rates
The fusion estimation is investigated in this paper for two-sensor discrete-time stochastic systems. A finite-horizon optimal linear estimator is designed for each sensor to generate local estimates with a nonuniform estimation rate. Then, a fusion rule with matrix weights in the linear minimum variance sense is designed for each sensor to fuse local estimates from itself and the other sensors. The proposed algorithm reduces to the one that can be used to design asynchronous fusion estimators with uncorrelated measurement noises. Finally, the effectiveness of the proposed results is illustrated by a simulation example of a maneuvering target tracking system.