Position Finding with Prior Knowledge of Covariance Parameters.

Abstract

Butterly presents a Bayesian approach as an alternative to the classical methods for solving the position-finding problem. Butterly assumes that bearing errors are independent and normally distributed with known variances. In the paper, the assumption of known variances is relaxed and it is shown that uncertainty about these variances can be incorporated into the model while also retaining the computational advantages of the Butterly formulation. It is also shown that the Bayes estimate and the classical maximum likelihood estimate will agree in certain cases.

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1979
Accession Number
ADA956151

Entities

People

  • Walter R. Nunn

Organizations

  • Center for Naval Analyses

Tags

DTIC Thesaurus Topics

  • Bayesian Networks
  • Covariance
  • Data Science
  • Flight Instruments
  • Ground Position Indicators
  • Information Science
  • Instrumentation
  • Measuring Instruments
  • Models
  • Navigational Equipment
  • Position Finding
  • Uncertainty

Fields of Study

  • Mathematics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms