摘要
针对网络化多传感器分布式估计中传感器能量和通信网络带宽约束问题,提出一种基于降低发送频率和数据压缩降维的分布式一致性融合估计算法.为了满足通信网络带宽要求,各传感器节点直接选取局部估计信号的部分分量进行传输;与此同时,各节点随机间歇式发送数据包到其他节点来节省能量.在给定一致性权重下,建立以一致性估计器增益为决策变量,以所有传感器节点有限时域下状态融合估计误差协方差矩阵的迹的和为代价函数的优化问题,基于Lyapunov稳定性理论给出使得融合估计误差在无噪声时渐近稳定的一致性估计器增益存在的充分条件,并通过最小化代价函数的上界得到一组次优的一致性估计器增益值.最后,通过算例仿真验证算法的有效性.
For the problem of sensor energy and communication networked bandwidth constraints in networked multisensor distributed estimation,a consensus-based fusion estimation algorithm by reducing transmission frequency and data dimensionality reduction is proposed.In order to meet the communication network bandwidth requirements,each sensor node randomly transmits partial components of the local estimation to other nodes.At the same time,each node randomly sends packets to other nodes for saving energy.For the given consensus weight,the optimization problem with the consensus estimator gain as the decision variable and the sum of the traces of the state fusion estimation error covariance matrix in the finite time domain of all sensor nodes as the cost function is established.Based on the Lyapunov stability theory,the sufficient condition for the existence of the consensus estimator gains which make the fusion estimation error without noise asymptotically stable is given.Then,a set of suboptimal estimator gains are obtained by minimizing the upper bound of the cost function.Finally,the effectiveness of the algorithm is verified by numerical examples.
作者
赵国荣
廖海涛
韩旭
王元鑫
ZHAO Guo-rong;LIAO Hai-tao;HAN Xu;WANG Yuan-xin(Coastal Defense College,Naval Aviation University,Yantai 264001,China)
出处
《控制与决策》
EI
CSCD
北大核心
2020年第1期16-24,共9页
Control and Decision
基金
国家自然科学基金项目(61473306).
关键词
网络化多传感器
分布式估计
一致性算法
能量和带宽约束
渐近稳定
估计器增益
networked multi-sensor
distributed estimation
consensus algorithm
energy and bandwidth constraints
asymptotically stability
estimator gains
作者简介
通讯作者:廖海涛,E-mail:haitao_liao@163.com.
