Consensus optimization approach for distributed Kalman filtering: Performance recovery of centralized filtering. (March 2023)

• Record Type: Journal Article
• Authors: Ryu, Kunhee; Back, Juhoon
• Is Part Of: Automatica. Volume 149(2023)
• Publication Date: 2023-03
• Subjects: Distributed Kalman filtering -- Distributed optimization -- Dual ascent method; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2022.110843
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This paper investigates the distributed Kalman filtering (DKF) from distributed optimization viewpoint. Motivated by the fact that Kalman filtering is a maximum a posteriori estimation (MAP) problem, which is a quadratic optimization problem, we reformulate DKF problem as a consensus optimization problem, resulting in that it can be solved by many existing distributed optimization algorithms. A new DKF algorithm employing the dual ascent method is proposed, and its stability is proved under mild assumptions. The performance of the proposed algorithm is evaluated through numerical experiments.