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CORR
2007
Springer

Distributing the Kalman Filter for Large-Scale Systems

9 years 2 months ago
Distributing the Kalman Filter for Large-Scale Systems
This paper derives a near optimal distributed Kalman filter to estimate a large-scale random field monitored by a network of N sensors. The field is described by a sparsely connected dynamical system of high-dimensionality, n. The main contributions of the paper are: (1) distribute the high-dimensional model into N coupled sensor-based reduced models of dimension nl n using a graph-theoretic approach; (2) implement local Kalman filters on the reduced models; (3) fuse the observations and estimates that are common among the local Kalman filters using bipartite fusion graphs and consensus averaging algorithms; (4) invert the error covariances and information matrices of the local filters with a generalized distributed matrix Jacobi algorithm that we introduce and an L−banded matrix inversion theorem. These inversion algorithms compute the submatrices of interest with only local variables of dimension nl, hence, performing the Riccati and Lyapunov equations with only local commun...
Usman A. Khan, José M. F. Moura
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2007
Where CORR
Authors Usman A. Khan, José M. F. Moura
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