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A Novel Case of Practical Exponential Observer Using Extended Kalman Filter
Ji DX(冀大雄)1; Deng, Zhi1; Li S(李硕)2; Ma, Dongfang1; Wang, Tao1; Song W(宋伟)1; Zhu, Shiqiang1; Wang, Zhi3; Pan, Hongjun4; Sharma, Sanjay5; Yang, Xu
Department水下机器人研究室
Source PublicationIEEE ACCESS
ISSN2169-3536
2018
Volume6Pages:58004-58011
Indexed BySCI ; EI
EI Accession number20183805835025
WOS IDWOS:000449002100001
Contribution Rank2
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China ; Fundamental Research Funds for the Central Universities ; U.K. Royal Society-International Exchanges 2017 Cost Share, China
KeywordDiscrete-time nonlinear system extended Kalman filter exponential observer restrictions spectral norm
AbstractThis technical note presents a case of practical exponential observer using extended Kalman filter (EKF) independent of certain restrictions, such as online check and estimation error of initial state. Recursive state estimation is usually a challenge for discrete-time nonlinear system in terms of computation cost. EKF is attractive with its simplicity since it is considered as an exponential observer given the above restrictions. However, those restrictions are so mathematically complicated that EKF cannot be practical in estimation. A novel case for an exponential observer using EKF is proposed, which is independent of such restrictions. However, these restrictions are proved to be unnecessary in the case. The proposed case is illustrated by a navigation system scenario. The validity of the case is demonstrated by a numerical simulation experiment. The system is deterministic.
Language英语
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS KeywordSTATE ESTIMATION ; COOPERATIVE NETWORKS ; NONLINEAR ESTIMATION ; SYSTEMS ; TRACKING
WOS Research AreaComputer Science ; Engineering ; Telecommunications
Funding ProjectNational Natural Science Foundation of China[51679213] ; National Key Research and Development Program of China[2016YFC0300801] ; Fundamental Research Funds for the Central Universities ; U.K. Royal Society-International Exchanges 2017 Cost Share, China[IEC\NSFC\170405]
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/23557
Collection水下机器人研究室
Corresponding AuthorJi DX(冀大雄)
Affiliation1.Ocean College, Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, Zhejiang University, Zhoushan 316000 China
2.The State Key Laboratory of Robotics, Shenyang Institute of Automation,CAS, Shenyang 110000 China
3.College of Control Science and Engineering, Zhejiang University, Zhoushan 316000 China
4.School of Mathematics Physics and Information Science, Zhejiang Ocean University, Zhoushan 316000 China
5.School of Engineering, Plymouth University, Plymouth,PL4 8AA UK
Recommended Citation
GB/T 7714
Ji DX,Deng, Zhi,Li S,et al. A Novel Case of Practical Exponential Observer Using Extended Kalman Filter[J]. IEEE ACCESS,2018,6:58004-58011.
APA Ji DX.,Deng, Zhi.,Li S.,Ma, Dongfang.,Wang, Tao.,...&Yang, Xu.(2018).A Novel Case of Practical Exponential Observer Using Extended Kalman Filter.IEEE ACCESS,6,58004-58011.
MLA Ji DX,et al."A Novel Case of Practical Exponential Observer Using Extended Kalman Filter".IEEE ACCESS 6(2018):58004-58011.
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