Robust Kalman Filters for Linear Time-Varying Systems
with Stochastic Parametric Uncertainties
Robust Kalman Filters for Linear Time-Varying Systems
with Stochastic Parametric Uncertainties
F. Wang and V. Balakrishnan
IEEE Trans. Signal Processing,
vol. 50, no. 4, pages 803-813, April 2002
Abstract:
We present a robust recursive Kalman filtering algorithm that addresses
estimation problems that arise in linear time-varying systems with
stochastic parametric uncertainties. The filter has a one-step
predictor-corrector structure and minimizes an upper bound of the
mean square estimation error at each step, with the minimization
reduced to a convex optimization problem based on linear matrix
inequalities. The algorithm is shown to converge when the system is
mean square stable and the state space matrices are time-invariant.
A numerical example, consisting of equalizer design for a
communication channel, demonstrates that our algorithm offers
considerable improvement in performance when compared to
conventional Kalman filtering techniques.
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