Distributed Fusion Estimation for Uncertain Systems with Cross-correlated Noises and Transmission Delays

    • Presentation speakers

    The information fusion estimation problems are investigated for uncertain systems with cross-correlated noises and data transmission delays. Based on Kalman filtering theory,a distributed fusion estimation scheme is proposed by distributed information perception and centralized fusion. To alleviate the communication burden and computational cost with network-induced transmission delays, the measurement transformation approach with re-organized innovation sequence is proposed. Depending on the fusion criterion, the optimal weighted fusion estimators are designed via minimizing error cross-covariance theory to reduce information redundancy and maintain the higher measurement accuracy. An illustrative example is given to validate the effectiveness of the proposed method.


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