Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems. (3rd November 2009)

• Record Type: Journal Article
• Authors: Song, Il Young; Kim, Du Yong; Kim, Yong Hoon; Lee, Suk Jae; Shin, Vladimir
• Other Names: Gustafsson Fredrik Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2009(2009)
• Publication Date: 2009-11-03
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2009/929535
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum mean square error criterion. The key contribution of this paper lies in the derivation of the differential equations for determining the error cross-covariances between the local receding horizon Kalman filters. The subsequent application of the proposed distributed filter to a linear dynamic system within a multisensor environment demonstrates its effectiveness.