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Distributed Filtering Algorithm Based on Tunable Weights Under Untrustworthy Dynamics

机译:不可信动态下基于可调权重的分布式滤波算法

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摘要

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.
机译:针对不可信环境下传感器网络系统状态估计的有效融合,提出了一种基于可调权重的分布式滤波算法。考虑节点位置和节点对网络拓扑的影响,开发了一种分布式滤波算法来评估其确定性。首先使用权重分配方法,将被攻击节点的权重分配给其他完整节点以更新确定度,然后使用确定度组成的权重来优化共识协议以更新节点估计。所提算法不仅提高了分布式滤波的精度,而且提高了节点估计的一致性。仿真结果证明了所提算法的有效性。

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  • 来源
    《自动化学报(英文版)》 |2016年第2期|225-232|共8页
  • 作者单位

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

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

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

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

    School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;

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