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Time-Varying Noise Statistic Estimator Based Adaptive Simplex Cubature Kalman Filter
Joint Authors
Li, Zhaoming
Yang, Wenge
Ding, Dan
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-14
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
To address the problem that filtering accuracy is reduced with the inaccurate time-varying noise statistic in conventional cubature Kalman filter, a noise statistic estimator based adaptive simplex cubature Kalman filter is put forward in this paper.
First, the simplex cubature rule is adopted to approximate the intractable nonlinear Gaussian weighted integral in the filter.
Secondly, a suboptimal unbiased constant noise statistic estimator is derived based on the maximum a posteriori estimation criterion.
For the time-varying noise, the above estimator is modified using an exponential weighted attenuation method to realize the oblivion of stale data which results in a fading memory estimator, which has the ability to estimate the time-varying noise statistic to revise the filter online.
The simulation results indicate that the proposed filter can achieve higher accuracy than conventional filters with inaccurate noise statistic.
American Psychological Association (APA)
Li, Zhaoming& Yang, Wenge& Ding, Dan. 2017. Time-Varying Noise Statistic Estimator Based Adaptive Simplex Cubature Kalman Filter. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1190709
Modern Language Association (MLA)
Li, Zhaoming…[et al.]. Time-Varying Noise Statistic Estimator Based Adaptive Simplex Cubature Kalman Filter. Mathematical Problems in Engineering No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1190709
American Medical Association (AMA)
Li, Zhaoming& Yang, Wenge& Ding, Dan. Time-Varying Noise Statistic Estimator Based Adaptive Simplex Cubature Kalman Filter. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1190709
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190709