Robust Kalman filters for linear time-varying systems withstochastic parametric uncertainties

  • Authors:
  • Fan Wang;V. Balakrishnan

  • Affiliations:
  • Motorola Inc., Arlington Heights, IL;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2002

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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 with conventional Kalman filtering techniques