Reduced-Order Estimators and Their Application to Aircraft Navigation.

Abstract

Minimum-variance reduced-order estimators are derived and analyzed. Although the computations required to determine the optimum gains and dynamics for these optimal reduced-order filters and observer-estimators may be too complex to implement in real time, in many cases these parameters can be determined off-line and stored for real-time use. Furthermore, a study of optimal reduced-order estimators provides guidelines for designing simpler reduced-order filters and observer-estimators. Also, the error covariance matrices of the optimal reduced-order estimators provide quantitative criteria for measuring the performance of heuristically designed reduced-order estimators. Two multisensor navigation example problems are formulated and used for comparing the performance of a heuristically designed reduced-order filter to that of the corresponding minimum-variance reduced-order estimators. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1974
Accession Number
AD0921863

Entities

People

  • Joseph A. D'appolito
  • Julian L. Center
  • Steven I Marcus

Organizations

  • TASC, Inc

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aircrafts
  • Computational Complexity
  • Computations
  • Covariance
  • Data Science
  • Dynamics
  • Estimators
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Multisensors
  • Navigation
  • Observers
  • Statistical Algorithms

Readers

  • Computational Fluid Dynamics (CFD)
  • Phased Array Antenna Design.
  • Regression Analysis.