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Composite embedded cubature Kalman filter
Author(s) -
Meng Dong,
Miao Lingjuan,
Shao Haijun
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2797
Subject(s) - kalman filter , computer science , algorithm , filter (signal processing) , extended kalman filter , alpha beta filter , ensemble kalman filter , fast kalman filter , process (computing) , adaptive filter , invariant extended kalman filter , control theory (sociology) , moving horizon estimation , artificial intelligence , computer vision , control (management) , operating system
Summary The embedded cubature Kalman filter (ECKF) is proven as a kind of algorithm that has higher precision than cubature Kalman filter. Based on the ECKF, a new algorithm, named composite ECKF (CECKF), is presented in this paper. The new CECKF can increase filter precision by means of reusing the embedded cubature rule in the process of numerical approximation, which can realize higher precision than ECKF in theory. At the same time, another new algorithm, named adaptive CECKF, is also put forward by introducing an adaptive method based on CECKF. Through the comparison of simulation, the proposed methods are able to enhance filter precision.

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