A Frequency Domain Analysis of the Linear Discrete Kalman Filter

Abstract

The linear discrete Kalman filter was analyzed using a frequency domain approach. Process and measurement noise covariances are shown to be critical design parameters which, together with the assumed prior state and covariance estimates, completely determine the gain schedule of the linear Kalman filter. Several relevant design techniques are illustrated and discussed. The concepts of smoothing and sharpening are demonstrated. Extensions to adaptive, non-linear, and non-parametric filtering are briefly discussed, as are applications to inventory management, estimation of time-varying mean functions, and multiple regression.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1980
Accession Number
ADA085058

Entities

People

  • Walter J. Costello

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Adaptive Filters
  • Aircrafts
  • Data Analysis
  • Data Science
  • Filtration
  • Fourier Series
  • Frequency Domain
  • Gaussian Processes
  • Information Science
  • Kalman Filters
  • Linear Filtering
  • Markov Processes
  • Mathematical Filters
  • Random Variables
  • Recursive Filters
  • Statistics
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

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