Distributed Kalman Filtering for Interconnected Dynamic Systems
针对互联动态系统，设计仅利用自身和邻居信息的分布式卡尔曼滤波器，通过解耦策略降低互联项影响，并给出稳定性条件，最后用重型车辆队列验证效果。
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.