A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 3 Issue 2
Apr.  2016

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Shiming Chen, Xiaoling Chen, Zhengkai Pei, Xingxing Zhang and Huajing Fang, "Distributed Filtering Algorithm Based on Tunable Weights Under Untrustworthy Dynamics," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 2, pp. 225-232, 2016.
Citation: Shiming Chen, Xiaoling Chen, Zhengkai Pei, Xingxing Zhang and Huajing Fang, "Distributed Filtering Algorithm Based on Tunable Weights Under Untrustworthy Dynamics," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 2, pp. 225-232, 2016.

Distributed Filtering Algorithm Based on Tunable Weights Under Untrustworthy Dynamics


This work was supported by National Natural Science Foundation of China (61364017,60804066), The Scientific and Technological Project of Education Department of Jiangxi Province (KJLD12068), and Natural Science Foundation of Jiangxi Province (20132BAB201039).

  • Aiming at effective fusion of a system state estimate of sensor network under attack in an untrustworthy environment, distributed filtering algorithm based on tunable weights is proposed. Considering node location and node influence over the network topology, a distributed filtering algorithm is developed to evaluate the certainty degree firstly. Using the weight reallocation approach, the weights of the attacked nodes are assigned to other intact nodes to update the certainty degree, and then the weight composed by the certainty degree is used to optimize the consensus protocol to update the node estimates. The proposed algorithm not only improves accuracy of the distributed filtering, but also enhances consistency of the node estimates. Simulation results demonstrate the effectiveness of the proposed algorithm.


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