Zhang Yuchen, Chen Bo, Yu Li, Ho Daniel W C
IEEE Trans Cybern. 2022 Nov;52(11):11571-11580. doi: 10.1109/TCYB.2021.3072198. Epub 2022 Oct 17.
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.
本文关注互联动态系统的分布式卡尔曼滤波问题，其中每个子系统的局部估计器仅根据其自身信息和相邻信息进行设计。开发了一种解耦策略以最小化互联项对估计性能的影响，然后在最小均方误差意义下推导递归分布式卡尔曼滤波器。此外，通过使用线性时变系统的李雅普诺夫准则，给出了稳定性条件，使得所设计的估计器是有界的。最后，采用重型车辆编队系统来展示所提方法的有效性和优势。
