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Relative closeness ranking of Kalman filtering with multiple mismatched measurement noise covariances

文献类型：期刊论文

作者Shao, Teng1; Ge, Quanbo2,3; Duan, Zhansheng1; Yu, Junzhi3
刊名IET CONTROL THEORY AND APPLICATIONS
出版日期2018-05-22
卷号12期号:8页码:1133-1140
关键词Linear Systems Kalman Filters Mean Square Error Methods Relative Closeness Ranking Kalman Filtering Multiple Mismatched Measurement Noise Covariances Linear Dynamic Systems Ideal Mse Filter Calculated Mse True Mse Fmse Tmse Imse Mean Squared Error
DOI10.1049/iet-cta.2017.1088
文献子类Article
英文摘要Due to the complexity of practical systems, the used models generally mismatch the practical ones. For the Kalman filtering with a single mismatched measurement noise covariance, the ranking of the ideal MSE (IMSE), the filter calculated MSE (FMSE), and the true MSE (TMSE) has been established. This study considers the ranking of the relative closenesses from the FMSE and TMSE to the IMSE when multiple mismatched measurement noise covariances are used. It is found that for the case with two deviations of the same signs, the larger the absolute deviation is, the farther away the FMSE or TMSE is from the IMSE. It is also found that for the case with two deviations of different signs, if the positive deviations are less than the absolute value of the negative deviation, then the FMSE or TMSE with positive deviation is relatively closer to the IMSE. Otherwise the ranking of the two corresponding relative closenesses depends on the parallel sum of two deviations with a non-zero threshold. Then the pair-wised ranking of the relative closenesses corresponding to two arbitrary deviations is further extended to the case with more than two deviations. Numerical examples are provided to validate the results.
WOS关键词NONLINEAR-SYSTEMS ; NAVIGATION
WOS研究方向Automation & Control Systems ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000431111000012
资助机构Fundamental Research Funds for the Central Universities of China ; Zhejiang Provincial Nature Science Foundation of China(LR17F030005) ; Hangzhou Dianzi University ; Open Project Program of the State Key Laboratory of Management and Control for Complex Systems ; National Natural Science Foundation of China (NSFC)(61273037 ; 61333011 ; 61673317 ; 61773313)
源URL[http://ir.ia.ac.cn/handle/173211/22043]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
作者单位1.Xi An Jiao Tong Univ, Ctr Informat Engn Sci Res, Xian 710049, Shaanxi, Peoples R China
2.Hangzhou Dianzi Univ, Inst Syst Sci & Control Engn, Sch Automat, Hangzhou 310018, Zhejiang, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Shao, Teng,Ge, Quanbo,Duan, Zhansheng,et al. Relative closeness ranking of Kalman filtering with multiple mismatched measurement noise covariances[J]. IET CONTROL THEORY AND APPLICATIONS,2018,12(8):1133-1140.
APA Shao, Teng,Ge, Quanbo,Duan, Zhansheng,&Yu, Junzhi.(2018).Relative closeness ranking of Kalman filtering with multiple mismatched measurement noise covariances.IET CONTROL THEORY AND APPLICATIONS,12(8),1133-1140.
MLA Shao, Teng,et al."Relative closeness ranking of Kalman filtering with multiple mismatched measurement noise covariances".IET CONTROL THEORY AND APPLICATIONS 12.8(2018):1133-1140.

入库方式： OAI收割

来源：自动化研究所

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