Classification of Targets in SAR Images Using ISAR Data

Abstract

Feature-based classification of targets in SAR images by using ISAR measurements was studied, based on polarimetric SAR and ISAR data acquired with the MEMPHIS radar system of FGAN-FHR. The data contained one T-72 battle tank, one BMP combat vehicle, and several confusers. The resolution was 75 cm. Nine features were studied of which four were analyzed: area, coefficient of variation, weighted-rank fill ratio and VV/VH ratio. Of these features the only one that resulted in certain separability was the weighted-rank fill ratio. But to classify the targets using only one feature is not reliable, especially considering the resolution. Neighbor number and HH/HV ratio were successfully used to separate the targets from natural clutter false alarms.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA471111

Entities

People

  • A. C. Van Den Broek
  • J. J. De Wit
  • R. J. Dekker

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Classification
  • Depression Angles
  • Detection
  • Detectors
  • False Alarms
  • Frequency
  • Image Processing
  • Image Reconstruction
  • Ka Band
  • Machine Learning
  • Radar
  • Synthetic Aperture Radar
  • Target Classification
  • Target Recognition
  • Two Dimensional
  • Vehicles
  • Warning Systems

Readers

  • Computer Vision.
  • Radar Systems Engineering.