Convergence and Accuracy Analysis for a Distributed Static State Estimator Based on Gaussian Belief Propagation

• 成果类型: Article
• 署名作者: Marelli, Damian; Sui, Tianju; Fu, Minyue; Sun, Ximing
• 署名单位: Guangdong University of Technology; Dalian University of Technology; University of Newcastle
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3037454
• 发表日期: 2021
• 页码: 4785-4791
• 关键词: convergence; estimation; State estimation; Jacobian matrices; Distributed algorithms; large-scale systems; Belief propagation; Accuracy analysis; belief propagation (BP); convergence analysis; Distributed state estimation

摘要

This article focuses on the distributed static estimation problem. A belief propagation (BP) based estimation algorithm is studied for its convergence and accuracy. More precisely, we give conditions under which the BP-based distributed estimator is guaranteed to converge and we give concrete characterizations for its accuracy. Our results reveal new insights and properties of this distributed algorithm, leading to better theoretical understanding of static distributed state estimation and new applications of the algorithm.