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Abstrakty
In the paper, state filtration in a LQG problem formulated for a multisensor system is considered. Control is determined by a central node as a linear form of a state estimate. It is assumed that control values are not available to local nodes. Because of the drawbacks of centralized filtration an optimal fusion of decentralized local Kalman filters is proposed. When control values are not available to local nodes, then control should be treated as a random variable in the synthesis of local state estimates. This leads to a non-classical estimation. It is shown that the proposed filter is equivalent to the centralized one. (original abstract)
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autor
- Silesian Technical University
Bibliografia
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- Chen H.M., Kirubarajan T., Bar-Shalom Y. (2003) Performance limits on track to track fusion versus centralized estimation. "IEEE Trans. on Aerospace and Electronic Systems" 39, 386-400.
- Duan Z., Li X.R. (2011) Lossless Linear Transformation of Sensor Data for Distributed Estimation Fusion. "IEEE Trans. on Signal Proc." 59, 362-372.
- Hashemipour H., Roy S., Laub A.(1988) Decentralized Structures for Parallel Kalman Filtering. "IEEE Trans. Aut. Control" 33, 88-93.
- Liggins M.E., Chong C.Y., Kadar I., Alford M.G., Vannicola V., Thomopoulos S. (1997) Distributed Fusion Architectures and Algorithms for Target Tracking. "Proc. of the IEEE" 85, 95-107.
- Meditch J.S. (1969) Stochastic Optimal Linear Estimation and Control. Mc Graw-Hill, Inc.
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- Sijs J., Lazar M., Van den Bosch P.P.J., Papp Z. (2008) An overview of non-centralized Kalman filters. "Proc. of the 17th IEEE Int. Conf. On Control Appl." IEEE, 739-744.
- Schlosser M.S., Kroschel K. (2007) Performance analysis of decentralized Kalman Filters under Communication Constraints. "Journal of Advances in Information Fusion" 2, 65-75.
- Song E.B, Zhu Y.M., Zhou J., You Z.S. (2007) Optimal Kalman filtering fusion with cross-correlated sensor noises. "Automatica", 43, 1450-1456.
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Typ dokumentu
Bibliografia
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