Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems
Joint Authors
Gao, Zhaohui
Zhong, Yongmin
Gu, Chengfan
Mu, Dejun
Ren, Chengcai
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-17
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper presents a new adaptive random weighting cubature Kalman filtering method for nonlinear state estimation.
This method adopts the concept of random weighting to address the problem that the cubature Kalman filter (CKF) performance is sensitive to system noise.
It establishes random weighting theories to estimate system noise statistics and predicted state and measurement together with their associated covariances.
Subsequently, it adaptively adjusts the weights of cubature points based on the random weighting estimations to improve the prediction accuracy, thus restraining the disturbances of system noises on state estimation.
Simulations and comparison analysis demonstrate the improved performance of the proposed method for nonlinear state estimation.
American Psychological Association (APA)
Gao, Zhaohui& Mu, Dejun& Zhong, Yongmin& Gu, Chengfan& Ren, Chengcai. 2019. Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1195506
Modern Language Association (MLA)
Gao, Zhaohui…[et al.]. Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems. Mathematical Problems in Engineering No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1195506
American Medical Association (AMA)
Gao, Zhaohui& Mu, Dejun& Zhong, Yongmin& Gu, Chengfan& Ren, Chengcai. Adaptively Random Weighted Cubature Kalman Filter for Nonlinear Systems. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1195506
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195506