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Volume 3 Issue 2
Apr.  2016

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2016  >  3(2): 225-232
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.
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Distributed Filtering Algorithm Based on Tunable Weights Under Untrustworthy Dynamics

  • 1. School of Electrical and Electrical Engineering, East China Jiaotong University, Nanchang 330013, China;

  • 2. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China

Funds:

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).

    Abstract
  • 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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