PRIOR INFORMATION AND BIAS IN SEQUENTIAL ESTIMATION,

Abstract

This article applies discrete sequential filtering to estimation of an unknown vector x imbedded in nonstationary uncorrelated noise, when observations depend linearly on x in a time-varying manner. Such a situation occurs in trajectory determination close to the earth. We solve the recursive filter equations to obtain the n-th estimate of x, xn, and its convariance matrix Pn, in terms of the observations (zi, i=1, ..., n) and initial values xo, Po. These expressions illustrate how the a priori information can introduce bias into the sequential estimates.

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1967
Accession Number
AD0657754

Entities

People

  • Allen Klinger

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Cooperation
  • Equations
  • Filters
  • Filtration
  • Jet Propulsion
  • Observation
  • Recursive Filters
  • Trajectories

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Analytical Mechanics
  • Statistical inference.