Sparsity based regularization for microwave imaging with NESTA algorithm

We propose a sparsity based regularization method, Born Iterative Method(BIM)-NESTA to enhance the resolution in sparse microwave imaging problems. The inverse problem is handled with conjunction of Born Iterative Method and NESTA algorithm by minimization of the cost function which consists measurement-data misfit and first-norm penalty term. Numerical results verify that BIM-NESTA method manages to reconstruct closely located object and possess edge preserving capability for sparse domain where traditional BIM with Tikhonov regularization fails.