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A Seventh‐Degree Cubature Kalman Filter
Author(s) -
Meng Dong,
Miao Lingjuan,
Shao Haijun,
Shen Jun
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1537
Subject(s) - degree (music) , kalman filter , control theory (sociology) , mathematics , tracking (education) , filter (signal processing) , unscented transform , sampling (signal processing) , ensemble kalman filter , extended kalman filter , algorithm , computer science , statistics , artificial intelligence , computer vision , control (management) , psychology , pedagogy , physics , acoustics
The fifth‐degree cubature Kalman filter (CKF) has been proved to be a kind of algorithm that has higher precision than the third‐degree CKF and unscented Kalman filter (UKF). In order to further improve the performance of CKF, the seventh‐degree CKF is proposed in this paper by expanding the spherical‐radial rule, and a new kind of deterministic sampling method is derived based on the seventh‐degree cubature rule. Through the comparison in target tracking simulation, the seventh‐degree CKF methods are shown to be able to enhance filtering precision compared to the fifth‐degree CKF, the third‐degree CKF and the UKF filter.