An Adaptive Consensus Filter for Distributed State Estimation With Unknown Noise Statistics

被引：13
|
作者：
Dong, Xiangxiang [1 ,2 ,3 ]
Battistelli, Giorgio [4 ]
Chisci, Luigi [4 ]
Cai, Yunze [1 ,2 ,3 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Key Lab Syst Control & Informat Proc, Minist Educ, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Key Lab Marine Intelligent Equipment & Syst, Minist Educ, Shanghai 200240, Peoples R China
[4] Univ Florence, Dept Informat Engn, I-50139 Florence, Italy
来源：
IEEE SIGNAL PROCESSING LETTERS | 2021年 / 28卷
基金：
中国国家自然科学基金;
关键词：
Peer-to-peer computing; Noise measurement; Handheld computers; Covariance matrices; Bayes methods; Adaptive systems; Time measurement; Adaptive Kalman filter; sensor network; consensus; exponential-class densities; natural parameters; inverse Wishart distribution; variational Bayes (VB) method; DENSITIES;
D O I：
10.1109/LSP.2021.3099972
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：
An adaptive consensus filter
引用
收藏
页码：1595 / 1599
页数：5
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