Multiparametric Electromagnetic Inversion of 3-D Anisotropic Objects Embedded in Layered Media Based on Mixed $L_1$–$L_2$ Norm Regularization

In this letter, the mixed $L_1$–$L_2$ norm regularization is adopted to constrain the full-wave inversion solution of the multiparametric electromagnetic inverse scattering by the 3-D anisotropic objects. The mixed $L_1$–$L_2$ regularization term is added to the standard $L_2$ norm cost function in the framework of the Born iterative method. In each iteration, the mixed $L_1$–$L_2$ norm term is transformed into $L_2$ norm term through a weight matrix and the whole cost function is minimized by the conjugate gradient method. Numerical results show that, compared with the traditional Tikhonov $L_2$ regularization, the mixed $L_1$–$L_2$ regularization can achieve higher reconstruction accuracy without additional computational cost due to the structural similarity constraint among different model parameters.