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ASME Press Select Proceedings

International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)

Editor
V. E. Muhin
V. E. Muhin
National Technical University of Ukraine
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W. B. Hu
W. B. Hu
Wuhan University
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ISBN:
9780791859742
No. of Pages:
656
Publisher:
ASME Press
Publication date:
2011

Under the rule of minimizing the trace of estimation error covariance matrix, the optimal information fusion Kalman filter weighted by scalars or diagonal matrices for sequential processing is presented for the decentralized information fusion system with multiple sensors and correlated noises. This paper compares the estimation precision between the fusion filter and the local filters. And the result estimated by the fusion filter is better than the local filters. The simulation shows the feasibility and the validity of the estimation fusion algorithms.

Abstract
Keywords
Introduction
Problem Formulation
Sequential Fusion with Scalar Weights
Sequential Fusion with Diagonal Matrix Weights
The Anysis for Error Precision
Simulation
Conclusion
Acknowledgments
References
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