Stability analysis of distributed Kalman filtering algorithm for stochastic regression model
Siyu Xie1
Die Gan2
Zhixin Liu3
1.School of Aeronautics and Astronautic,University of Electronic Science and Technology of China,Chengdu 611731,Sichuan,China2.College of Artificial Intelligence,Nankai University,Tianjin 300350,China3.State Key Laboratory of Mathematical Sciences,Academy of Mathematics and Systems Science,Beijing 100190,China;School of Mathematical Sciences,University of Academy of Sciences,Beijing 100049,China
摘要：The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysis of the proposed distributed KF algorithm without independent and stationary signal assumptions,which implies that the theoretical results are able to be applied to stochastic feedback systems.Note that the main difficulty of stability analysis lies in analyzing the properties of the product of non-independent and non-stationary random matrices involved in the error equation.We employ analysis techniques such as stochastic Lyapunov function,stability theory of stochastic systems,and algebraic graph theory to deal with the above issue.The stochastic spatio-temporal cooperative information condition shows the cooperative property of multiple sensors that even though any local sensor cannot track the time-varying unknown signal,the distributed KF algorithm can be utilized to finish the filtering task in a cooperative way.At last,we illustrate the property of the proposed distributed KF algorithm by a simulation example.
机标关键词：distributedalgorithmstabilitykalmananalysismodelfilteringregression
论文发表日期：2025-05-30
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：15( 161-175 )
英文信息