A Minimization Method for Engineering Estimation,

Abstract

This paper obtains a convergence-criterion for optimal estimation by constructing a mathematical theory of ordering, based upon topological and algebraic concepts. This theory provides the model for minimizing the variance of error associated with the estimators of a true state. Thus it is a supplement to the classical Kalman filtering approach. The theory is first described in mathematical terms, as an ordering structure consisting of these entities: a non-empty set of estimators, a binary relation of comparison between estimators, and a closed binary operation that composes the estimators in some prescribed fashion. A triple consisting of these entities of an ordering structure, if and only if the axioms of weak order, associativity, monotonocity, and Archimedean property are satisfied. A weak representation theorem is stated regarding the existence of an order-preserving real-valued function on the set of estimators.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADP002372

Entities

People

  • Shilpa S. Dhar

Organizations

  • Lockheed Martin Missiles and Space

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Engineering
  • Estimators
  • Filters
  • Filtration
  • Kalman Filtering
  • Mathematical Filters
  • Mathematics
  • Optimal Estimators
  • Statistical Algorithms

Fields of Study

  • Mathematics

Readers

  • Computational Linguistics
  • Mathematical Modeling and Probability Theory.
  • Statistical inference.