An augmented lagrangian method for sparse SAR imaging

In this paper, we present a solution to the constrained l1-norm minimization problem for sparse SAR imaging. The technique we present relies on recent advances in the solution of optimization problems, based on Augmented Lagrangian Methods (ALMs), namely the Alternating Direction Method of Multipliers. Here, we present an application of C-SALSA (an ALM for constrained optimization problems) to SAR imaging, and introduce a new weighting scheme to improve the sparsity of the reconstructions. We then compare the performances of several techniques to understand the effectiveness of ALMs in the context of SAR imaging.