Application of Bayesian Networks to Midcourse Multi-Target Tracking

Abstract

This presentation discusses the application of Bayesian Networks or Influence Diagrams to the implementation of midcourse tracking algorithms. The Influence Diagram is used to represent and manipulate probabilistic information in complex networks of random variables. The generic capabilities of the Influence Diagram are used to carry out eh major tracking functions, including linear gaussian state estimation, data association hypothesis scoring and track promotion scoring.

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Document Details

Document Type
Technical Report
Publication Date
Aug 03, 1989
Accession Number
ADA339011

Entities

People

  • Michael Kovacich

Organizations

  • Lockheed Martin Missiles and Space

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Data Association
  • Mathematics
  • Multitarget Tracking
  • Random Variables
  • Statistical Algorithms
  • Target Tracking
  • Three Dimensional

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference