In this paper, a distributed estimation algorithm using Bayesian-based forward backward Kalman filter (KF) is proposed for stochastic singular linear systems. The method incorporates generalised versions of KF for bounded cases with complete and incomplete prior information, followed by estimation fusion of these cases. The incorporated filters remain optimal given the cross-covariance of the local estimates. The proposed approach is validated on a coupled-tank system.
Inspec keywords: belief networks; stochastic systems; Kalman filters; linear systems
Other keywords: coupled tank system; Bayesian based forward backward Kalman filter; cross-covariance; stochastic singular linear systems; enhanced distributed estimation algorithm; KF
Subjects: Combinatorial mathematics; Filtering methods in signal processing; Signal processing theory; Time-varying control systems
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