Cart (Loading....) | Create Account
Close category search window

Avoiding local minima in entropy-based SAR autofocus

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Morrison, R.L. ; Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA ; Munson, D.C., Jr. ; Do, M.N.

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.

Published in:

Statistical Signal Processing, 2003 IEEE Workshop on

Date of Conference:

28 Sept.-1 Oct. 2003

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.