{"title":"分布式卡尔曼滤波耦合动力学的最优协同监测策略","authors":"Charles Z. Liew, Raymond Shaw, Shi‐Dan Sun","doi":"10.1109/ICIST.2014.6920347","DOIUrl":null,"url":null,"abstract":"In this brief paper, coupled heterogeneous dynamic has been discussed and an optimal co-estimation with distributed Kalman filter strategy is proposed for monitoring such dynamic with consideration of incomplete information scenario. The experiment result shows that proposed co-estimation strategy obtains better effect to estimate the state of coupled heterogeneous monitoring under the noisy environment compared to separate DKF.","PeriodicalId":306383,"journal":{"name":"2014 4th IEEE International Conference on Information Science and Technology","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal co-monitoring strategy for coupled dynamics with distributed Kalman filtering\",\"authors\":\"Charles Z. Liew, Raymond Shaw, Shi‐Dan Sun\",\"doi\":\"10.1109/ICIST.2014.6920347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this brief paper, coupled heterogeneous dynamic has been discussed and an optimal co-estimation with distributed Kalman filter strategy is proposed for monitoring such dynamic with consideration of incomplete information scenario. The experiment result shows that proposed co-estimation strategy obtains better effect to estimate the state of coupled heterogeneous monitoring under the noisy environment compared to separate DKF.\",\"PeriodicalId\":306383,\"journal\":{\"name\":\"2014 4th IEEE International Conference on Information Science and Technology\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 4th IEEE International Conference on Information Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIST.2014.6920347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 4th IEEE International Conference on Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST.2014.6920347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal co-monitoring strategy for coupled dynamics with distributed Kalman filtering
In this brief paper, coupled heterogeneous dynamic has been discussed and an optimal co-estimation with distributed Kalman filter strategy is proposed for monitoring such dynamic with consideration of incomplete information scenario. The experiment result shows that proposed co-estimation strategy obtains better effect to estimate the state of coupled heterogeneous monitoring under the noisy environment compared to separate DKF.