Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99369
Title: Diffusion Kalman filtering based on covariance intersection
Authors: Hu, Jinwen
Xie, Lihua
Zhang, Cishen
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2011
Source: Hu, J., Xie, L., & Zhang, C. (2011). Diffusion Kalman Filtering Based on Covariance Intersection. IEEE Transactions on Signal Processing, 60(2), 891-902.
Series/Report no.: IEEE transactions on signal processing
Abstract: This paper is concerned with distributed Kalman filtering for linear time-varying systems over multiagent sensor networks. We propose a diffusion Kalman filtering algorithm based on the covariance intersection method, where local estimates are fused by incorporating the covariance information of local Kalman filters. Our algorithm leads to a stable estimate for each agent regardless of whether the system is uniformly observable locally by the measurements of its neighbors which include the measurements of itself as long as the system is uniformly observable by the measurements of all the agents and the communication is sufficiently fast compared to the sampling. Simulation results validate the effectiveness of the proposed distributed Kalman filtering algorithm.
URI: https://hdl.handle.net/10356/99369
http://hdl.handle.net/10220/13504
ISSN: 1053-587X
DOI: http://dx.doi.org/10.1109/TSP.2011.2175386
Rights: © 2011 IEEE
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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