Loading...

L2-Regularized Iterative Weighted Algorithm for Inverse Scattering

Azghani, M ; Sharif University of Technology

686 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/TAP.2016.2546385
  3. Publisher: Institute of Electrical and Electronics Engineers Inc
  4. Abstract:
  5. We propose a new inverse scattering technique based on sparsity for the application of microwave imaging. The underdetermined inverse problem appeared in the distorted born iterative method (DBIM) technique is solved using the suggested L2-regularized iterative weighted algorithm (L2-IWA). The L2-regularizer has been introduced to stabilize the algorithm against nonlinear approximations, and the sparsity is enforced with the aid of another reweighted L2-norm regularizer to address the ill-posedness of the inverse problem. The derived algorithm is a three-step iterative technique which solves the underdetermined set of equations at each DBIM iteration. Moreover, the convergence of the L2-IWA technique is proved, analytically. The suggested method outperforms its other counterparts in various scenarios of homogeneous and heterogeneous breast models. Besides improving the resolution of the breast tumors, the L2-IWA technique is shown to be robust against additive noise
  6. Keywords:
  7. Compressed sensing ; Sparsity, inverse scattering ; Additive noise ; Algorithms ; Approximation algorithms ; Inverse problems ; Tomography ; Distorted Born iterative methods ; Ill-posedness ; Inverse scattering ; Iterative technique ; Iterative-weighted ; Microwave imaging ; Microwave tomography ; Nonlinear approximation ; Iterative methods
  8. Source: IEEE Transactions on Antennas and Propagation ; Volume 64, Issue 6 , 2016 , Pages 2293-2300 ; 0018926X (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/7440811