Target-Centric Probabilistic Multi-Hypothesis Tracking

Abstract

This report examines an alternative assignment model for Probabilistic Multi-Hypothesis Tracking (PMHT) in which targets are assigned to measurements, in contrast to the original PMHT model in which measurements are assigned to targets. A new target-centric PMHT algorithm is derived and compared to its original measurement-centric counterpart. The relationship between target-centric PMHT and the probabilistic data association (PDA) filter for single-target tracking in clutter was examined, and a PDA-style approximation to the target state covariance matrices for target-centric PMHT is proposed. A target-centric/measurement-centric PMHT hybrid is also proposed to address algorithm performance in the case of closely spaced targets.

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Document Details

Document Type
Technical Report
Publication Date
Jun 12, 2020
Accession Number
AD1120646

Entities

People

  • Michael J. Walsh
  • Tod Luginbuhl

Organizations

  • Naval Undersea Warfare Center

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Covariance
  • Data Association
  • Data Processing
  • Data Science
  • Detection
  • Detectors
  • Estimators
  • Filtration
  • Information Science
  • Kalman Filtering
  • Kalman Filters
  • Measurement
  • Multiple Hypothesis Tracking
  • Multiple Targets
  • Multitarget Tracking
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms
  • Target Detection
  • Target Tracking
  • Undersea Warfare
  • Warfare

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.

Technology Areas

  • Space
  • Space - Space Objects