SUB-OPTIMAL GAIN SCHEDULES FOR THE DISCRETE KALMAN FILTER.

Abstract

The object of this study is to find an approximation to the discrete optimal Kalman filter gain schedule by closed-form analytic expressions. In doing so, required table storage and/or on-line computation time can be reduced at little expense in terms of filter performance degradation. The method of least squares was used to determine the closed-form solution which was the best fit to the discrete Kalman filter gain schedule. The criterion for performance degradation was the difference between the values of the diagonal elements of the estimation covariance matrix, obtained by using the Kalman gain schedule, and the corresponding values obtained by using the closed-form analytic expressions for the elements of the gain matrix. Examples are presented to show that near-optimal results were obtained using this method. A comparison of the results of this study with another near-optimal estimation scheme is also included. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1969
Accession Number
AD0703263

Entities

People

  • Robert Allen Crotteau

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Computational Complexity
  • Computations
  • Covariance
  • Data Science
  • Degradation
  • Filters
  • Information Science
  • Kalman Filters
  • Mathematical Analysis
  • Mathematical Filters
  • Mathematics
  • Statistical Algorithms
  • Statistical Analysis

Fields of Study

  • Engineering

Readers

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