Fourier-Domain Multichannel Autofocus for Synthetic Aperture Radar
Authors:
- 19 May 2011
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 20 (12) , 3544-3552
Abstract
Synthetic aperture radar (SAR) imaging suffers from image focus degradation in the presence of phase errors in the received signal due to unknown platform motion or signal propagation delays. We present a new autofocus algorithm, termed Fourier-domain multichannel autofocus (FMCA), that is derived under a linear algebraic framework, allowing the SAR image to be focused in a noniterative fashion. Motivated by the mutichannel autofocus (MCA) approach, the proposed autofocus algorithm invokes the assumption of a low-return region, which generally is provided within the antenna sidelobes. Unlike MCA, FMCA works with the collected polar Fourier data directly and is capable of accommodating wide-angle monostatic SAR and bistatic SAR scenarios. Most previous SAR autofocus algorithms rely on the prior assumption that radar's range of look angles is small so that the phase errors can be modeled as varying along only one dimension in the collected Fourier data. And, in some cases, implicit assumptions are made regarding the SAR scene. Performance of such autofocus algorithms degrades if the assumptions are not satisfied. The proposed algorithm has the advantage that it does not require prior assumptions about the range of look angles, nor characteristics of the scene.Keywords
This publication has 13 references indexed in Scilit:
- MCA: A Multichannel Approach to SAR AutofocusIEEE Transactions on Image Processing, 2009
- Fourier-domain Multichannel Autofocus for synthetic aperture radar2008
- Overcoming polar-format issues in multichannel SAR Autofocus2008
- Phase Gradient Autofocus for SAR Phase Correction: Explanation and Demonstration of Algorithmic Steps2005
- Aberration correction by maximizing generalized sharpness metricsJournal of the Optical Society of America A, 2003
- Autofocusing of ISAR images based on entropy minimizationIEEE Transactions on Aerospace and Electronic Systems, 1999
- Perfect blind restoration of images blurred by multiple filters: theory and efficient algorithmsIEEE Transactions on Image Processing, 1999
- Multichannel blind identification: from subspace to maximum likelihood methodsProceedings of the IEEE, 1998
- EVAM: an eigenvector-based algorithm for multichannel blind deconvolution of input colored signalsIEEE Transactions on Signal Processing, 1995
- Eigenvector method for maximum-likelihood estimation of phase errors in synthetic-aperture-radar imageryJournal of the Optical Society of America A, 1993