Distributed Kalman Filtering for Interconnected Dynamic Systems

This article is concerned with the distributed Kalman filtering problem for interconnected dynamic systems, where the local estimator of each subsystem is designed only by its own information and neighboring information. A decoupling strategy is developed to minimize the impact of interconnected terms on the estimation performance, and then the recursive and distributed Kalman filter is derived in the minimum mean-squared error sense. Moreover, by using Lyapunov criterion for linear time-varying systems, stability conditions are presented such that the designed estimator is bounded. Finally, a heavy duty vehicle platoon system is employed to show the effectiveness and advantages of the proposed methods.

Automated summary

This article addresses the distributed Kalman filtering problem for interconnected dynamic systems by developing a decoupling strategy to minimize the impact of interconnected terms on estimation performance. The recursive and distributed Kalman filter is derived in the minimum mean-squared error sense, with stability conditions presented using Lyapunov criterion. The effectiveness and advantages of the proposed methods are demonstrated using a heavy duty vehicle platoon system.