A Physics-Constrained Neural Network for Electromagnetic Inverse Scattering Imaging (opens in new tab)

To accurately and robustly solve electromagnetic inverse scattering problems (ISPs), a physics-constrained neural network (PCNN) method is proposed in this work. The method adopts the Born iteration framework, where a neural network is embedded in each iteration to solve the optimization problem. It combines the linearization capability of traditional inverse methods with the powerful capability of neural networks in solving complex optimization tasks. In the neural network, the $L_{2}$ norm ...