On the Effects of the Initial Condition in State Estimation for Discrete-Time Linear Systems

Abstract

We consider the one step prediction problem for discrete time linear systems in correlated Gaussian white plant and observation noises, and non-Gaussian initial conditions. Explicit representations are obtained for the MMSE and LLSE (or Kalman) estimates of the state given past observations, as well as for the expected square of their difference. These formulae are obtained with the help of the Girsanov transformation for Gaussian white noise sequences, and explicitly display the effects of the distribution of the initial condition. With the help of these formulae, we investigate the large time asymptotics of epsilon sub t, the expected squared difference between the MMSE and LLSE estimates at time t. We characterize the limit of the error sequence {epsilon sub t, t = 1,2,... } and obtain some related rates of convergence. A complete large time analysis is provided for the scalar case.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADA454943

Entities

People

  • Armand M. Makowski
  • Richard B. Sowers

Organizations

  • University of Maryland

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DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • California
  • Classification
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  • Linear Systems
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  • Noise
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  • White Noise

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Linear Algebra