In this paper we present a new method for restoring multi-pass synthetic aperture radar (SAR) images containing arbitrary gaps in SAR phase history data. Frequency and aspect gaps in SAR image spectrum manifest themselves as artifacts in the associated SAR imagery. Our approach, which we term LDREG for the (cursive ell);₁ difference regularization, jointly processes multi-pass interrupted data using sparse magnitude and sparse magnitude difference constraints, and results in improved quality imagery. We find that the joint processing of LDREG results in coherent change detection gains over independent processing of each data pass. To illustrate the capabilities of LDREG, we evaluate coherent change detection performance using images from the Gotcha SAR.

Date Published: 23 May 2013
PDF: 9 pages
Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, 87460L (23 May 2013); doi: 10.1117/12.2020653

Published in SPIE Proceedings Vol. 8746:
Algorithms for Synthetic Aperture Radar Imagery XX
Edmund Zelnio; Frederick D. Garber, Editor(s)