An augmented Lagrangian method for complex-valued compressed SAR imaging

Warning The system is temporarily closed to updates for reporting purpose.

Güven, H. Emre and Güngör, Alper and Çetin, Müjdat (2016) An augmented Lagrangian method for complex-valued compressed SAR imaging. IEEE Transactions on Computational Imaging, 2 (3). pp. 235-250. ISSN 2333-9403

This is the latest version of this item.

[thumbnail of 151202_ALM_complex_SAR_twocolumn_submitted.pdf] PDF
151202_ALM_complex_SAR_twocolumn_submitted.pdf
Restricted to Repository staff only

Download (18MB) | Request a copy
[thumbnail of guven_TCI16.pdf] PDF
guven_TCI16.pdf
Restricted to Registered users only

Download (2MB) | Request a copy

Abstract

In this paper, we present a solution to the complex synthetic aperture radar (SAR) imaging problem within a constrained optimization formulation where the objective function includes a combination of the ℓ1-norm and the total variation of the magnitude of the complex valued reflectivity field. The technique we present relies on recent advances in the solution of optimization problems, based on Augmented Lagrangian Methods, and in particular on the Alternating Direction Method of Multipliers (ADMM). We rigorously derive the proximal mapping operators, associated with a linear transform of the magnitude of the reflectivity vector and magnitude-total-variation cost functions, for complex-valued SAR images, and thus enable the use of ADMM techniques to obtain computationally efficient solutions for radar imaging. We study the proposed techniques with multiple features (sparse and piecewise-constant in magnitude) based on a weighted sum of the 1-norm and magnitude-total-variation. We derive a fast implementation of the algorithm using only two transforms per iteration for problems admitting unitary transforms as forward models. Experimental results on real data from TerraSAR-X and SARPER-airborne SAR system developed by ASELSAN-demonstrate the effectiveness of the proposed approach.
Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Müjdat Çetin
Date Deposited: 12 Nov 2016 14:12
Last Modified: 22 May 2019 13:43
URI: https://research.sabanciuniv.edu/id/eprint/30321

Available Versions of this Item

Actions (login required)

View Item
View Item