{"title":"具有一步自相关噪声的多速率系统的最优滤波","authors":"Tian Tian, Shuli Sun","doi":"10.1109/ICEDIF.2015.7280149","DOIUrl":null,"url":null,"abstract":"The optimal filtering problem is addressed for multi-rate systems with one-step auto-correlated noises. The state is updated at the highest sampling rate and the sensor has a lower sampling rate. System noise and measurement noise are one-step auto-correlated, respectively. An optimal filter in the linear minimum variance sense is proposed via an innovation analysis approach. A simulation example is given to show the effectiveness of the proposed algorithms.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal filtering for multi-rate systems with one-step auto-correlated noises\",\"authors\":\"Tian Tian, Shuli Sun\",\"doi\":\"10.1109/ICEDIF.2015.7280149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The optimal filtering problem is addressed for multi-rate systems with one-step auto-correlated noises. The state is updated at the highest sampling rate and the sensor has a lower sampling rate. System noise and measurement noise are one-step auto-correlated, respectively. An optimal filter in the linear minimum variance sense is proposed via an innovation analysis approach. A simulation example is given to show the effectiveness of the proposed algorithms.\",\"PeriodicalId\":355975,\"journal\":{\"name\":\"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEDIF.2015.7280149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEDIF.2015.7280149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal filtering for multi-rate systems with one-step auto-correlated noises
The optimal filtering problem is addressed for multi-rate systems with one-step auto-correlated noises. The state is updated at the highest sampling rate and the sensor has a lower sampling rate. System noise and measurement noise are one-step auto-correlated, respectively. An optimal filter in the linear minimum variance sense is proposed via an innovation analysis approach. A simulation example is given to show the effectiveness of the proposed algorithms.
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