A Contrast-Source Electromagnetic Imaging Scheme Based on Projected Nonlinear Landweber–Kaczmar

An electromagnetic imaging (EMI) framework is proposed based on contrast-source (CS) formulation. The CS data and state misfits are cast to form a multi-cost problem. The framework implements a nonlinear Landweber–Kaczmarz (LWKZ) algorithm that conveys the multi-cost minimization. The iteration step lengths associated with the cost terms are updated based on the maximum eigenvalues of the cost terms’ Jacobian matrices. Unlike in other CS schemes, preconditioning is not required in the proposed CS-based LWKZ (CSLWKZ), as the eigenvalues balance the cost terms through each iteration step. Furthermore, an efficient approach to calculate the eigenvalues is outlined, which significantly reduces the CSLWKZ computations. At the end of the CSLWKZ scheme, a first-norm projection operator is enforced on the contrast vector to achieve sparseness. Numerical results of a range of validity tests and a comparison with three other CS frameworks demonstrate the efficiency of the proposed approach. In addition, experimental results based on the Fresnel Institute database are illustrated.