A distributed Kalman filter for a class of large-scale interconnected systems

This paper studies the problem of designing distributed state estimators for a class of large-scale interconnected systems. The goal is to design a local state estimator for each subsystem using local information and state estimates exchanged from neighboring subsystems. A Kalman-like distributed estimation strategy is considered where the interacting terms from neighboring subsystems are replaced with their estimates. We first show that this Kalman-like distributed estimator is not always stable, a property always enjoyed by the standard Kalman filter. Then several sufficient conditions are provided for testing the stability of the distributed estimator.