Advanced Automatic Target Recognition

Abstract

The grant supported research on techniques for recognizing targets in visible, infrared, laser radar, synthetic aperture radar and high-range aperture radar data. Empirical probability density functions of 'probe values' gives rise to a method of estimating probability that a target of known shape is present. Two-stage Constant False Alarm rate detectors were introduced to reduce the PA rate in the presence of SAR speckled images. A complete algorithm for wide-area site models using polarimetric SAR was developed. Multiscale methods were introduced into HRR classification with an improvement in performance. Operator-theoretic methods were successfully employed in the important area of detection and location of roads and nearby targets.

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Document Details

Document Type
Technical Report
Publication Date
Sep 05, 1997
Accession Number
ADA335690

Entities

People

  • Azriel Rosenfeld

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computer Vision
  • Detection
  • Detectors
  • False Alarms
  • High Resolution
  • Image Processing
  • Laser Radar
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Recognition
  • Synthetic Aperture Radar
  • Target Classification
  • Target Recognition
  • Warning Systems

Readers

  • Computer Vision.
  • Radar Systems Engineering.

Technology Areas

  • Directed Energy