Multistage Estimation of Bias States in Linear Systems.

Abstract

This paper provides an alternate, constructive derivation of Friedland's method (Ref 1) for recursive bias filtering; and, extends his method to the case where we may wish to increase (or decrease) the number of biases. We show that it is possible to add (or delete) bias states in such a manner that previously computed quantities can be used to obtain new estimates of the dynamical state vector and the now-larger bias vector. Adding (or deleting) bias states is important when, for example, the bias states are used to model constant, but unknown, instrumentation error sources, of which there can be a large number. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1977
Accession Number
ADA039764

Entities

People

  • H. D. Washburn
  • J. M. Mendel

Organizations

  • University of Southern California

Tags

Communities of Interest

  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Automatic
  • Differential Equations
  • Electrical Engineering
  • Engineering
  • Equations
  • Estimators
  • Filters
  • Filtration
  • Kalman Filters
  • Linear Systems
  • New York
  • Optimal Estimators
  • Plastic Explosives
  • Security
  • Square Roots

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.