Network Level Association and Fusion of Kinematic and Attribute Information

Abstract

This work investigates the various criteria for track-to-track association/fusion (T2TA/F): likelihood ratios and distance criteria. Procedures to obtain the quantities needed by the LR criterion from the limited information available from the real world communication networks are developed. Algorithms for T2TA/F with heterogeneous sensors and investigation of several assignment algorithms for the T2TA problem are carried out. Procedures for simultaneous handling of continuous valued (kinematic and feature) states and discrete valued ones (attribute/classification) for an integrated approach to the Track Association and Fusion problem are presented.

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 2010
Accession Number
ADA545335

Entities

People

  • Yaakov Bar-Shalom

Organizations

  • University of Connecticut

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Detectors
  • Algorithms
  • Control Systems
  • Data Association
  • Data Fusion
  • Data Processing
  • Detection
  • Detectors
  • Ground Vehicles
  • Identification
  • Impact Point
  • Monopulse Radar
  • Multitarget Tracking
  • Sensor Networks
  • Signal Processing
  • Target Tracking
  • Warning Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.