This paper addresses distributed state estimation in a peer-to-peer heterogeneous sensor network characterized by varying qualities of local estimators. The proposed approach employs weighted Kullback–Leibler average of local posteriors, considering both and protocols to efficiently disseminate information throughout the network. Our consensus and flooding methods extend communication and fusion to include designed local weighting factors. In addition, we present a unified framework for flooding, tailored to accommodate networks with arbitrarily limited communication bandwidth. By applying these methods to average local posteriors, we derive consensus-based and flooding-based distributed state estimators. Stability of the proposed estimators is analyzed for linear systems under network connectivity and system observability. Finally, simulation results demonstrate the effectiveness of the proposed approach.

中文翻译：

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异构传感器网络的分布式状态估计


本文讨论了点对点异构传感器网络中的分布式状态估计，其特征是局部估计器质量不同。所提出的方法采用局部后验的加权 Kullback-Leibler 平均值，同时考虑和协议以在整个网络中有效地传播信息。我们的共识和洪泛方法扩展了通信和融合，以包括设计的本地权重因子。此外，我们还提出了一个统一的泛洪框架，专为适应通信带宽任意有限的网络而定制。通过将这些方法应用于平均局部后验，我们推导出基于共识和基于洪泛的分布式状态估计器。对网络连接和系统可观测性下的线性系统所提出的估计器的稳定性进行了分析。最后，仿真结果证明了该方法的有效性。