摘要
研究带宽受限下的基于一致性的分布式融合估计问题.建立以一致性滤波增益为决策变量,以所有传感器有限时域下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.在给定一致性权重的前提下,给出使得系统融合估计误差在无噪声时渐近稳定的一致性滤波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滤波增益.最后通过算例仿真验证了所提出方法的有效性.
The consensus-based distributed fusion estimation problem with communication bandwidth constraints is investigated. An optimization problem which sets the consensus filter gains and the sum of the traces of all sensors＇ finite horizon estimation error covariance matrices to be the decision variables and the cost function, respectively, is established.For given consensus weights, sufficient conditions for the existence of the consensus filter gains which makes the dynamics of the estimation errors without noise asymptotically stable are given. Then, a set of sub-optimal consensus filter gains are computed by minimizing an upper bound of the cost function. Finally, simulation example is given to illustrate the effectiveness of the proposed approach.
出处
《控制与决策》
EI
CSCD
北大核心
2016年第12期2155-2162,共8页
Control and Decision
基金
国家自然科学基金项目(61473306)
关键词
一致性滤波
带宽受限
融合节点
渐近稳定
代价函数
consensus filter
communication bandwidth constraints
fusion node
asymptotically stable
cost function
