# Nonlinear Iterative Hard Thresholding for Inverse Scattering

## TL;DR

This paper introduces a nonlinear iterative hard thresholding algorithm for reconstructing sparse scatterers in inverse scattering problems, with analysis of convergence and error, supported by numerical simulations.

## Contribution

It presents a novel nonlinear generalization of iterative hard thresholding tailored for inverse scattering, with theoretical convergence analysis.

## Key findings

- Convergence of the proposed method is established through coherence estimates.
- Numerical simulations validate the effectiveness of the algorithm.
- The method outperforms traditional approaches in sparse inverse scattering reconstruction.

## Abstract

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.