A Multi-hop Sensor Network-based State Estimation for Discrete-time Linear Systems with Dynamic Communication Graphs

In this work, we propose a novel distributed estimation scheme for discrete-time linear time-invariant (LTI) systems. This scheme achieves finite-time convergence without introducing high gain. Each local observer can reconstruct the state of the global system by combining its local measurement with the information shared among the communication network. The scheme relies on the application of cross-agent communication technology which, while introducing potential communication delays, eliminates the need for centralized redesign when the network topology changes. The latter significantly benefits the flexibility of the proposed scheme, especially in the context of a time-varying communication topology. The numerical example validates the effectiveness of the proposed design and its robustness against communication delays.