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Kalman Filtering Algorithm for Systems with Stochastic Nonlinearity Functions, Finite-Step Correlated Noises, and Missing Measurements
Joint Authors
He, Yonghui
Jiang, Jibin
Huang, Hischuan
Zhuo, Shufang
Wu, Yanfeng
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The locally optimal filter is designed for a class of discrete-time systems subject to stochastic nonlinearity functions, finite-step correlated noises, and missing measurements.
The multiplicative noises are employed to describe the random disturbances in the system model.
The phenomena of missing measurements occur in a random way and the missing probability is characterized by Bernoulli distributed random variables with known conditional probabilities.
Based on the projection theory, a class of Kalman-type locally optimal filter is constructed and the filtering error covariance matrix is minimized in the sense of minimum mean square error principle.
Also, by solving the recursive matrix equation, we can obtain the filter gain.
Finally, two examples are provided: one is a numerical example to illustrate the feasibility and effectiveness of the proposed filtering scheme; the other is to solve the problem of target estimation for a tracking system considering networked phenomena.
American Psychological Association (APA)
He, Yonghui& Jiang, Jibin& Huang, Hischuan& Zhuo, Shufang& Wu, Yanfeng. 2018. Kalman Filtering Algorithm for Systems with Stochastic Nonlinearity Functions, Finite-Step Correlated Noises, and Missing Measurements. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1152263
Modern Language Association (MLA)
He, Yonghui…[et al.]. Kalman Filtering Algorithm for Systems with Stochastic Nonlinearity Functions, Finite-Step Correlated Noises, and Missing Measurements. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1152263
American Medical Association (AMA)
He, Yonghui& Jiang, Jibin& Huang, Hischuan& Zhuo, Shufang& Wu, Yanfeng. Kalman Filtering Algorithm for Systems with Stochastic Nonlinearity Functions, Finite-Step Correlated Noises, and Missing Measurements. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1152263
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152263