A new computationally efficient algorithm for reconstruction of lossy and inhomogeneous 1-D media by using inverse scattering method in time domain is proposed. In this algorithm, cosine Fourier series expansion is utilized in conjunction with finite difference time domain (FDTD) and particle swarm optimization (PSO) methods. The performance of the proposed algorithm is studied for several 1-D permittivity and conductivity profile reconstruction cases. Various types of regularization terms are examined and compared with each other in the presented method. It is shown that the number of unknowns in optimization routine is reduced to about 1/3 as compared with conventional methods which leads to a considerable reduction in the amount of computations, while the precision of the solutions would not be affected significantly. Another advantage of the proposed expansion method is that, since only a limited number of terms are taken in the expansion, the divergence of the algorithm is far less likely to occur. Sensitivity analysis of the suggested method to the number of expansion terms in the algorithm is studied, as well.
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