Kalman Filter Modeling

Abstract

The main emphasis of this tutorial paper is on the formulation of appropriate state-space models for Kalman filtering applications. The so-called "model" is completely specified by four matrix parameters and the initial conditions of the recursive equations. Once these are determined, the die is cast, and the way in which the measurements are weighted is determined forever after. Thus, finding a model that fits the physical situation at hand is all important. Also, it is often the most difficult aspect of designing a Kalman filter. Formulation of discrete state models from the spectral density and ARMA random process descriptions is discussed. Finally, it is pointed out that many common processes encountered in applied work (such as band-limited white noise) simply do not lend themselves very well to Kalman filter modeling.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1984
Accession Number
ADA495220

Entities

People

  • R. G. Brown

Organizations

  • Iowa State University

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Computers
  • Covariance
  • Engineering
  • Equations
  • Information Operations
  • Kalman Filters
  • Markov Processes
  • Mathematics
  • Measurement
  • Noise
  • Sequences
  • Spectra
  • Time Intervals
  • Transitions
  • White Noise

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space