Robust Receivers

Abstract

We considered two SAR applications: robust detection in the presence of motion through resolution cells (MTRC); and clutter classification. To overcome the loss of detection performance due to MTRC, we account for the MTRC blurring in the reconstructed image domain rather than in the image formation stage. This leads to a much simpler detector than in current approaches. Our geometric approach avoids the costly step of undoing the MTRC blurring, a step that is as costly as phase corrections in traditional SAR methods. Performance analysis and experimental studies with synthetic data show that the wavelet-based detector is robust and exhibits better detection performance than other common detectors, e.g., the correlator or the energy detector. Regarding clutter classification, we designed an algorithm that best matches (in the sense of the Bhattacharyya coefficient) wavelet packet bases to a family of random processes. This family accounts for the variability in the clutter. We tested our robust classifier with polarimetric SAR data with good results.

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Document Details

Document Type
Technical Report
Publication Date
Jun 07, 2001
Accession Number
ADA391458

Entities

People

  • Jose M. Moura

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Covariance
  • Data Science
  • Detection
  • Detectors
  • Engineering
  • Frequency
  • Image Processing
  • Images
  • Information Science
  • Machine Learning
  • Order Statistics
  • Radar
  • Signal Processing
  • Synthetic Aperture Radar
  • Target Detection

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Parasitology and Pharmacology of Malaria.