南京信息工程大学学报2025，Vol.17Issue(2)：273-281,9.DOI:10.13878/j.cnki.jnuist.20230523002
事件触发调度下带有动态偏差的传感器网络分布式融合状态估计
Distributed fusion state estimation for sensor networks with dynamic bias under event-triggered scheduling
摘要
Abstract
This paper investigates the event-triggered distributed filtering problem for a class of linear systems with additive and multiplicative noises transmitted over sensor networks,in which the considered process noise and meas-urement noise exhibit one-step autocorrelation and two-step cross-correlation characteristics.Firstly,a recursive equation is used to describe the dynamic bias of the system,and random variables following a Bernoulli distribution are introduced to characterize the random packet loss phenomenon.Secondly,an event-triggered mechanism is intro-duced to reduce the information transmission frequency while ensuring filtering performance,and a novel consistency-based distributed filter is constructed.Then,a recursive equation for the upper bound of filtering error covariance is established using stochastic analysis techniques,and an expression for filtering gain is derived by mini-mizing the variance constraint index.Finally,the effectiveness of the proposed optimized filtering method is verified through numerical simulations.关键词
传感器网络/递推分布式滤波/事件触发机制/相关噪声/动态偏差Key words
sensor networks/recursive distributed filtering/event-trigger mechanism/correlated noises/dynamical bias分类
计算机与自动化引用本文复制引用
王有刚,武怀勤..事件触发调度下带有动态偏差的传感器网络分布式融合状态估计[J].南京信息工程大学学报,2025,17(2):273-281,9.基金项目
国家自然科学基金(12171416) （12171416）
