Multitarget Multisensor Tracking Problems. Part 1. A General Solution and a Unified View on Bayesian Approaches

Abstract

Based upon a general target sensor model which allows dependence among targets and state-dependent target detection, a Bayesian solution to the multitarget tracking problem is derived. When this solution is applied to a special class of models, a less general but more implementationally feasible class of algorithms is obtained. Representative existing algorithms are then compared with our results. Doing so provides a unified view on Bayesian approaches to the multitarget tracking problem. Part I covers most of the analytical results, while in Part II, hypothesis management and other issues pertaining to implementation of multitarget algorithms are discussed with several examples.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1984
Accession Number
ADA197554

Entities

People

  • Chee-yee Chong
  • Edison Tse
  • Richard P. Wishner
  • Shozo Mori

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Batch Processing
  • Bayesian Networks
  • Data Association
  • Detection
  • Detectors
  • Heuristic Methods
  • Information Science
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Nomenclature
  • Probability Density Functions
  • Probability Distributions
  • Statistics
  • Stochastic Processes
  • Target Tracking
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Sensor Fusion and Tracking Systems.
  • Statistical inference.

Technology Areas

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