This paper is concerned with the distributed state estimation problem over sensor networks with a careful eye towards unknown inputs and quantized communication. Based on singular value decomposition, a unified estimator is developed to simultaneously estimate system states and unknown inputs, in which the estimator gain is determined by minimizing an upper bound on the updated error covariance. Then, a novel distributed state estimator is constructed by enforcing that each node uniformly quantizes the local estimates and the upper bounds on local error covariances before transmission. Furthermore, it is proved that the fused estimation error in each node is uniformly bounded in mean square. Finally, an illustrative example is provided to show the practical effectiveness of the proposed techniques.

中文翻译：

---

量化通信下传感器网络的分布式同步状态输入估计

本文关注传感器网络上的分布式状态估计问题，并仔细关注未知输入和量化通信。基于奇异值分解，开发了统一估计器来同时估计系统状态和未知输入，其中估计器增益是通过最小化更新的误差协方差的上限来确定的。然后，通过强制每个节点在传输之前统一量化局部估计和局部误差协方差的上限，构建了一种新颖的分布式状态估计器。进一步证明了每个节点的融合估计误差均方一致有界。最后，提供了一个说明性示例来展示所提出技术的实际有效性。