.png){kind=icon}
.png){kind=icon}
Return
Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm
.png){kind=icon}
OA
AI
DOI：10.1109/TGRS.2017.2681184.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
An efficient electromagnetic inversion scheme for imaging sparse 3-D domains is proposed. The scheme achieves its efficiency and accuracy by integrating two concepts. First, the nonlinear optimization problem is constrained using L-0 or L-1-norm of the solution as the penalty term to alleviate the ill-posedness of the inverse problem. The resulting Tikhonov minimization problem is solved using nonlinear Landweber iterations (NLW). Second, the efficiency of the NLW is significantly increased using a steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without sacrificing the convergence of the algorithm. Numerical results demonstrate the efficiency and accuracy of the proposed imaging scheme in reconstructing sparse 3-D dielectric profiles.
Keywords:
Accelerated steepest descent
electromagnetic imaging
electromagnetic inverse scattering
Landweber iterations
nonlinear ill-posed problem
numerical methods
sparsity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.6
Papers:
2.1W
Citations:
10.7W