Avoiding local minima in entropy-based SAR autofocus

R. L. Morrison, D. C. Munson, M. N. Do

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper explores the problem of avoiding local minima solutions in entropy-based synthetic aperture radar (SAR) autofocus. These autofocus algorithms correct defocused SAR images by determining the phase error estimate that produces the image with minimum entropy. However, the optimization strategy may converge to local minima solutions that correspond to incorrect image restorations. We propose two methods for reducing the likelihood of achieving such solutions. The first is a novel wavelet-based decomposition technique that determines the neighborhood of the global entropy minimum. A second strategy is the application of simulated annealing techniques to the optimization. We explore the performance of these methods using simulated SAR data, and provide a justification for how they work. Worst case phase errors in which the phase is random and uncorrelated between elements are considered.

Original languageEnglish (US)
Title of host publicationProceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)0780379977
StatePublished - 2003
EventIEEE Workshop on Statistical Signal Processing, SSP 2003 - St. Louis, United States
Duration: Sep 28 2003Oct 1 2003

Publication series

NameIEEE Workshop on Statistical Signal Processing Proceedings


OtherIEEE Workshop on Statistical Signal Processing, SSP 2003
Country/TerritoryUnited States
CitySt. Louis


  • Computer errors
  • Entropy
  • Error correction
  • Frequency
  • Image converters
  • Image reconstruction
  • Image restoration
  • Phase estimation
  • Simulated annealing
  • Synthetic aperture radar

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications


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