Journal
AUTOMATICA
Volume 50, Issue 5, Pages 1521-1525Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2014.03.002
Keywords
Optimal filtering; Networked systems; Sensor gain; Stochastic degradation; Recursive algorithms
Funding
- National Basic Research Program of China (973 Program) [201003731800]
- National Natural Science Foundation of China [61210012, 61290324, 61273156]
- Jiangsu Provincial Key Laboratory of E-business at Nanjing University of Finance and Economics of China [JSEB201301]
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In this paper, the optimal filtering problem is investigated for a class of networked systems in the presence of stochastic sensor gain degradations. The degradations are described by sequences of random variables with known statistics. A new measurement model is put forward to account for sensor gain degradations, network-induced time delays as well as network-induced data dropouts. Based on the proposed new model, an optimal unbiased filter is designed that minimizes the filtering error variance at each time-step. The developed filtering algorithm is recursive and therefore suitable for online application. Moreover, both currently and previously received signals are utilized to estimate the current state in order to achieve a better accuracy. A numerical simulation is exploited to illustrate the effectiveness of the proposed algorithm. (c) 2014 Elsevier Ltd. All rights reserved.
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