This paper investigates the problem of resilient distributed state estimation for a linear system in multi-hop communication networks. First, we introduce a graph-theoretic property, called multiple-hop strong robustness, to formalize the notion of communication and measurement redundancy in multi-hop communication networks. Second, we propose multi-hop communication-based resilient distributed state estimation strategies in the synchronous network and the asynchronous network with time delays, respectively. We provide necessary and sufficient conditions on the network topologies under which the regular agents can still asymptotically estimate the state vector of the system despite the existence of adversarial agents using the property of multiple-hop strong robustness. In contrast to the 1-hop communication-based strategies in the existing results, the proposed multi-hop communication-based strategies can reduce the communication redundancy requirement on the network and accelerate convergence. Finally, we present two examples to verify the effectiveness of the proposed strategies.

中文翻译：

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具有多跳通信的弹性分布式状态估计


本文研究了多跳通信网络中线性系统的弹性分布式状态估计问题。首先，我们引入称为多跳强鲁棒性的图论属性，以形式化多跳通信网络中的通信和测量冗余的概念。其次，我们分别在同步网络和时滞异步网络中提出了基于多跳通信的弹性分布式状态估计策略。我们在网络拓扑上提供了充分必要条件，在该条件下，尽管存在对抗性代理，但利用多跳强鲁棒性的特性，常规代理仍然可以渐近估计系统的状态向量。与现有结果中基于一跳通信的策略相比，所提出的基于多跳通信的策略可以减少网络上的通信冗余要求并加速收敛。最后，我们提出两个例子来验证所提出策略的有效性。