The MLE Tracking Algorithm: A Summary and Error Analysis.

Abstract

This report discusses, in general, least-squares tracking algorithms and in particular the maximum likelihood estimator (MLE). Its primary concern is a detailed error analysis both from a deterministic point of view (sensitivity study) and a stochastic viewpoint (state variable covariance matrix). The latter results are shown to be equivalent to a Cramer-Rao bound, and their relationship to Kalman filters is cited. Various subtleties of interpretation are discussed including several theorems on confidence ellipsoids. Examples generated by computer software based on the theory are also presented. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 15, 1981
Accession Number
ADA103427

Entities

People

  • M. J. Shensa

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Covariance
  • Data Science
  • Ellipsoids
  • Equations
  • Error Analysis
  • Errors
  • Estimators
  • Filters
  • Kalman Filters
  • Mathematical Filters
  • Random Variables
  • Sensitivity
  • Standards
  • Statistical Analysis
  • Statistics

Readers

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