Efficient Multiple Hypothesis Tracking by Track Segment Graph

Abstract

Multiple hypothesis tracking (MHT) addresses difficult tracking problems by maintaining alternative association hypotheses until enough good data e.g., features, are collected to select the correct hypotheses. Traditional MHT's cannot track targets over long durations because they frequently generate too many hypotheses to maintain the correct ones with the available processing resources. Track segment graph provides a compact and efficient representation of the key ambiguities in long term tracking. It is used to generate the long term track hypotheses that are evaluated to select the best long term global hypothesis. Simulation examples demonstrate the efficiency and optimality of the approach.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA534187

Entities

People

  • Chee-yee Chong
  • Greg Castanon
  • Guruswami Ravichandran
  • Nathan Cooprider
  • Shozo Mori

Organizations

  • BAE Systems

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Ambiguity
  • Data Association
  • Detectors
  • Efficiency
  • False Alarms
  • Hypotheses
  • Military Research
  • Multiple Hypothesis Tracking
  • Multiple Targets
  • Multitarget Tracking
  • Probability
  • Probability Distributions
  • Probability Hypothesis Density Filters
  • Simulations
  • Target Tracking

Readers

  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.