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

作　　者：王有刚[1] 武怀勤[2] WANG Yougang;WU Huaiqin(Department of Mathematics and Artificial Intelligence,Lyuliang University,Lyuliang 03300l,China;School of Science,Yanshan University,Qinhuangdao 066004,China)

机构地区：[1]吕梁学院数学与人工智能系,吕梁033001 [2]燕山大学理学院,秦皇岛066004

出　　处：《南京信息工程大学学报》2025年第2期273-281,共9页Journal of Nanjing University of Information Science & Technology

基　　金：国家自然科学基金(12171416)。

摘　　要：本文研究了一类基于传感器网络传输的具有加性和乘性噪声的线性系统的事件触发分布式滤波问题,并且所考虑的过程噪声和测量噪声具有一步自相关且两步交叉相关特性.首先,利用一个递推方程描述系统的动态偏差,并采用伯努利分布的随机变量刻画随机丢包现象.其次,引入事件触发机制在确保滤波性能的前提下降低信息传输频率,构造基于一致性的新型分布式滤波器.再次,利用随机分析技术建立滤波误差协方差上界的递推方程并通过最小化方差约束指标,给出滤波增益的表达式.最后,通过数值仿真验证了所提出的优化滤波方法的有效性.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 measurement 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 introduced 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 minimizing 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 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]