In this investigation we thoroughly analyze phase errors in synthetic aperture radar data, comparing our results to classic autofocusing algorithms, and propose a joint image formation and phase estimation algorithm based on high order total variation and phase synchronization. Our technique models the true correlation of phase errors, while enforcing smoothness and sharpness of edges within the scene. Numerical results show that our autofocusing technique is robust to various phase errors, phase wrappings, and noise.

This presentation is part of Contributed Presentation “CP8 - Contributed session 8”

Authors:

Theresa Scarnati (Air Force Research Laboratory)

Anne Gelb (Dartmouth College )

Keywords:

image deblurring, image reconstruction, inverse problems, nonlinear optimization, synthetic aperture radar