Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12962
Title: Kalman filtering for discrete stochastic systems with multiplicative noises and random two-step sensor delays
Authors: Chen, D
Yu, Y
Xu, L
Liu, X
Issue Date: 2015
Citation: Discrete Dynamics in Nature and Society, Article ID 809734, (2015)
Abstract: This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE). Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.
URI: http://bura.brunel.ac.uk/handle/2438/12962
DOI: http://dx.doi.org/10.1155/2015/809734
ISSN: 1026-0226
1607-887X
Appears in Collections:Dept of Mathematics Research Papers

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