2 research outputs found
A Linear Method for Shape Reconstruction based on the Generalized Multiple Measurement Vectors Model
In this paper, a novel linear method for shape reconstruction is proposed
based on the generalized multiple measurement vectors (GMMV) model. Finite
difference frequency domain (FDFD) is applied to discretized Maxwell's
equations, and the contrast sources are solved iteratively by exploiting the
joint sparsity as a regularized constraint. Cross validation (CV) technique is
used to terminate the iterations, such that the required estimation of the
noise level is circumvented. The validity is demonstrated with an excitation of
transverse magnetic (TM) experimental data, and it is observed that, in the
aspect of focusing performance, the GMMV-based linear method outperforms the
extensively used linear sampling method (LSM)
Linearized 3-D Electromagnetic Contrast Source Inversion and Its Applications to Half-space Configurations
One of the main computational drawbacks in the application of 3-D iterative
inversion techniques is the requirement of solving the field quantities for the
updated contrast in every iteration. In this paper, the 3-D electromagnetic
inverse scattering problem is put into a discretized finite-difference
frequency-domain scheme and linearized into a cascade of two linear
functionals. To deal with the nonuniqueness effectively, the joint structure of
the contrast sources is exploited using a sum-of--norm optimization
scheme. A cross-validation technique is used to check whether the optimization
process is accurate enough. The total fields are, then, calculated and used to
reconstruct the contrast by minimizing a cost functional defined as the sum of
the data error and state error. In this procedure, the total fields in the
inversion domain are computed only once, while the quality and accuracy of the
obtained reconstructions are maintained. The novel method is applied to
ground-penetrating radar imaging and through-the-wall imaging, in which the
validity and efficiency of the method is demonstrated