A Hybrid Born Iterative Bayesian Inversion Method for Electromagnetic Imaging of Moderate-Contrast Scatterers With Piecewise Homogeneities

To tackle the problem of imaging moderate-contrast scatterers with piecewise homogeneities, a hybrid Born iterative (BI) Bayesian inversion method is proposed. First, we establish the nonlinear inverse scattering problem in the context of multiple measurement vector (MMV). Then, a computationally efficient BI formulation is used to account for the strong nonlinear relationship between the scattered field and the contrast. In each iteration, a regularization strategy that exploits the piecewise homogeneous
$a$
priori information of the investigated domain is adopted to overcome the ill-posedness. Our proposed method can tackle the inverse scattering problem in its full nonlinearity and incorporate the available
$a$
priori information to stabilize the inversion procedure. Several representative tests are carried out to evaluate the performance of the proposed method. It is demonstrated that the proposed method outperforms other existing state-of-the-art algorithms in terms of accuracy, convergence, robustness, and computational efficiency.