Nonlinear Iterative Hard Thresholding for Inverse Scattering
It provides a new algorithm for sparse scatterer reconstruction in inverse scattering, but the results are incremental as they extend existing iterative hard thresholding to a nonlinear setting without demonstrating broad SOTA improvements.
The paper tackles the inverse scattering problem for sparse scatterers by proposing a nonlinear generalization of iterative hard thresholding, with convergence and error analyzed via coherence estimates and validated through numerical simulations.
We consider the inverse scattering problem for sparse scatterers. An image reconstruction algorithm is proposed that is based on a nonlinear generalization of iterative hard thresholding. The convergence and error of the method was analyzed by means of coherence estimates and compared to numerical simulations.