Multiresolution EO/IR Target Tracking and Identification

Abstract

Simultaneous target tracking and identification through feature association, attribute matching, or blob analysis is dependent on spatio-temporal measurements. Improved track maintenance should be achievable by maintaining coarse sensor resolutions on maneuvering targets and utilizing finer sensor resolutions to resolve closely-spaced targets. There are inherent optimal resolutions for sensors and restricted altitudes that constrain operational performance that a sensor manager must optimize for both wide-area surveillance and precision tracking. The advent of better optics, coordinated sensor management, and fusion strategies provide an opportunity to enhance simultaneous tracking and identification algorithms. We investigate utilizing electro-optical (EO) and Infrared (IR) sensors operating at various resolutions to optimize target tracking and identification. We use a target-dense maneuvering scenario to highlight the performance gains with the Multiresolution EO/IR data association (MEIDA) algorithm in tracking crossing targets.

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Document Details

Document Type
Technical Report
Publication Date
Feb 12, 2005
Accession Number
ADA438682

Entities

People

  • Bart Kahler
  • Erik Blasch

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Data Association
  • Detection
  • Detectors
  • High Resolution
  • Identification
  • Low Resolution
  • Mathematics
  • Measurement
  • Moving Targets
  • Multitarget Tracking
  • Probability
  • Recognition
  • Surveillance
  • Target Recognition
  • Target Tracking

Readers

  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Space
  • Space - Space Objects