An Accelerated Nonlinear Contrast Source Inversion Scheme For Sparse Electromagnetic Imaging

TL;DR

This paper introduces an accelerated nonlinear inversion method for electromagnetic imaging of sparse domains, combining Landweber iterations with an adaptive steepest descent algorithm to improve efficiency and accuracy.

Contribution

It presents a novel nonlinear inversion scheme that directly addresses non-linearity using NLW iterations combined with an adaptive algorithm for enhanced performance.

Findings

Demonstrates high accuracy in electromagnetic imaging of sparse domains.

Shows improved efficiency over traditional methods.

Validates applicability through numerical experiments.

Abstract

An efficient nonlinear contrast source inversion scheme for electromagnetic imaging of sparse two-dimensional investigation domains is proposed. To avoid generating a sequence of linear sparse optimization problems, the non-linearity is directly tackled using the nonlinear Landweber (NLW) iterations. A self-adaptive projected accelerated steepest descent (A-PASD) algorithm is incorporated to enhance the efficiency of the NLW iterations. The algorithm enforces the sparsity constraint by projecting the result of each steepest descent iteration into the L1-norm ball and selects the largest-possible iteration step without sacrificing from convergence. Numerical results, which demonstrate the proposed schemes accuracy, efficiency, and applicability, are presented.