OPTIMAL SAMPLING DISTRIBUTIONS FOR BAYES ESTIMATION OF RE-ENTRY PARAMETERS.

Abstract

Real time Bayesian estimation of the parameters of a non-linear dynamic system, such as a ballistic vehicle undergoing atmospheric re-entry, requires that the evaluation algorithm converge as rapidly as possible. One possible method for the evaluation of the Bayes estimate is by the use of Monte Carlo procedures. This report investigates the conditions necessary for the most rapid convergence of the Monte Carlo procedures for the evaluation of the Bayes estimate. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1966
Accession Number
AD0802152

Entities

People

  • R. B. Mcghee
  • R. B. Walford

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Sampling
  • Test And Evaluation

Readers

  • Aerospace Test and Evaluation
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference