Distributed Cooperative State Estimation for Dynamically Changing Networked Navigation

Matthew Howard and Zhihua Qu

Abstract:	In this paper, two new Cooperative Kalman-Bucy filters are derived using the matrix theoretic consensus based approach to cooperative control. The first is a centralized design of Cooperative Kalman-Bucy filter for which stabilizing and optimal gains are found to minimize error state covariance. Further, a distributed design of Cooperative Kalman-Bucy filter is also proposed by explicitly accounting for available information. Both designs of the proposed new Cooperative Kalman-Bucy filter can be applied to a team of heterogeneous time-varying systems within an incomplete, unidirectional communications network, and the overall estimation performance is superior to individual Kalman filters as long as better sensors are located at globally reachable nodes.
Published in:	Proceedings of IEEE/ION PLANS 2016 April 11 - 14, 2016 Hyatt Regency Hotel Savannah, GA
Pages:	987 - 993
Cite this article:	Howard, Matthew, Qu, Zhihua, "Distributed Cooperative State Estimation for Dynamically Changing Networked Navigation," Proceedings of IEEE/ION PLANS 2016, Savannah, GA, April 2016, pp. 987-993. https://doi.org/10.1109/PLANS.2016.7479799
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