The Design of an Optimal Observer for Linear Discrete Time Dynamical Systems.

Abstract

This report investigates the idea of utilizing Luenberger's minimal-order observer as an alternate to the Kalman filter for obtaining state estimates in linear discrete time stochastic systems. More specifically, this dissertation presents a solution to the problem of construction as optimal minimal order observer for linear discrete time stochastic systems where optimality is in the mean square sense. The approach taken in this report leads to a completely unified theory for the design of optimal minimal-order observers and is applicable to both time-varying and time-invariant linear systems. To illustrate the theory and application of the observer designs developed in the dissertation, the problem of designing a radar tracking system is considered. Examples are included which illustrate clearly the practicality and usefulness of the proposed optimal observer design technique. Finally, a host of topics for future research is presented in the hope of stimulating further research in the domain of observer theory.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1978
Accession Number
ADA072066

Entities

People

  • C. T. Leondes
  • L. M. Novak

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Complexity
  • Computational Science
  • Data Rate
  • Engineering
  • Equations
  • Equations Of State
  • Estimators
  • Kalman Filtering
  • Kalman Filters
  • Linear Systems
  • Optimal Estimators
  • Radar
  • Radar Tracking
  • Steady State
  • White Noise

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design