Robust median consensus cubature Kalman filter for distributed sensor networks

被引:1
作者
Zhou, Yufan [1 ]
Jing, Zhongliang [1 ]
Dong, Peng [1 ]
Huang, Jianzhe [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Aeronaut & Astronaut, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Consensus protocols; Median consensus; Consensus filter; Distributed sensor networks;
D O I
10.1016/j.dsp.2024.104629
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Distributed estimation of multiagent systems has gained increasing attention in recent years, with consensus algorithms being one of the popular research topics. However, most existing algorithms aim to reach a consensus on the average value of all nodes, which can be significantly affected by outliers and disturbances. To achieve a more resilient distributed estimation, this paper focuses on the median value consensus strategy. Specifically, a continuous median consensus method with an adaptive parameter is presented and discretized using timevarying steps. This approach eliminates chattering errors caused by discretization and enhances convergence speed considerably. Furthermore, utilizing the proposed algorithm, a median consensus cubature Kalman filter (MC-CKF) is designed for nonlinear scenarios. Simulation results demonstrate that our proposed algorithm outperforms traditional algorithms when facing a denial -of -service attack.
引用
收藏
页数:9
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