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Distributed fusion filter for networked stochastic uncertain systems with transmission delays and packet dropouts

机译:具有传输延迟和丢包的网络随机不确定系统的分布式融合滤波器

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This paper is concerned with the distributed fusion filtering problem for networked stochastic uncertain systems with white multiplicative noises. The measured data of each sensor are transmitted to the local processor over different communication channels with different one-step delay and packet dropout rates. At each moment, the local processor may receive one or two data packets or nothing. Local filters at individual local processors are transmitted to the fusion center to produce a fusion filter. First, a new augmented model with a lower-dimension state vector is developed. Based on the new augmented model, the local optimal linear filter is designed in the linear minimum variance sense. Then, the cross-covariance matrices between any two local filtering errors are derived to compute the fusion weights. At last, the distributed fusion filter is obtained based on the well-known fusion algorithm weighted by matrices in the linear minimum variance sense. Moreover, the steady-state behavior of the proposed distributed fusion filter is analyzed.
机译:本文涉及具有白色乘法噪声的网络随机不确定系统的分布式融合滤波问题。每个传感器的测量数据通过不同的通信通道以不同的单步延迟和丢包率传输到本地处理器。在每个时刻,本地处理器可能会接收到一个或两个数据包,或者什么也没有。各个本地处理器上的本地过滤器被传输到融合中心以产生融合过滤器。首先,开发了具有较低维状态向量的新的增强模型。基于新的增强模型,在线性最小方差意义上设计了局部最优线性滤波器。然后,得出任意两个局部滤波误差之间的互协方差矩阵,以计算融合权重。最后,基于线性最小方差意义上的矩阵加权加权融合算法,得到分布式融合滤波器。此外,分析了所提出的分布式融合滤波器的稳态行为。

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