A General Theory for Bayesian Multitarget Tracking and Classification - Generalized Tracker/Classifier (GTC)

Abstract

A general theory for the tracking and classification of multiple targets using a Bayesian approach is presented, together with its specialization to independent, identically distributed target models. The implementation of the theory is through the Generalized Tracker/Classifier. Simulation results to illustrate the algorithm are also given.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 07, 1982
Accession Number
ADA122618

Entities

People

  • C. Y. Chong
  • E. Tse
  • R. P. Wishner
  • S. Mori

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Computational Science
  • Data Association
  • Detectors
  • Filtration
  • Gaussian Distributions
  • Kalman Filters
  • Machine Learning
  • Mathematical Filters
  • Monte Carlo Method
  • Moving Target Indicator Radar
  • Multitarget Tracking
  • Radar
  • Random Variables
  • Sensor Networks
  • Wireless Sensor Networks

Readers

  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference