Electrical conductivity imaging using dual-frequency EM data based on Tikhonov regularization
基于Tikhonov正则化的双频电磁波电导率成像反演

Using a combination of Tikhonov regularization and active-set method, this paper introduces an algorithm to numerically resolve electrical conductivity imaging equation using dual-frequency EM data, so that we develop not only the existing algorithms, but also its implementation. The linear-equation system, however, generated from dual-frequency electrical conductivity imaging, is exceedingly ill-posed, and this paper just focuses on its resolution. Considering the non-negativity of the electrical conductivity, we introduce a proper regularization parameter to reduce the problem to a non-negative least square problem, and then solve it with active-set algorithm. Afterwards some numerical examples are carried out to test the validity of the proposed method. And finally, we implement it to the actual inversion problem of conductivity imaging using dual-frequency EM data, and gain satisfactory results compared to normal methods such as LSQR, SP-LSQR and shear Tikhonov regularization.