The present contribution deals with a reconstruction approach to the inverse electromagnetic scattering problem based on the joint exploitation of the deterministic linear inversion and global optimization strategies. The deterministic approach is based on the Born iterative method (BIM) enhanced by regularization techniques, such as Algebraic Reconstruction Technique (ART) and Conjugate Gradient (CG). In the second step of the overall strategy, a stochastic global optimization approach, the genetic algorithm (GA), is carried out. In this way, we will benefit from the regularization schemes and address the local minima problem. Numerical results are presented with reference to the permittivity reconstructions in the case of a homogeneous cylinder and an inhomogeneous layered cylinder.
A Combination of Deterministic Regularizations and Genetic Algorithms in Two-dimentional Inverse Scattering Problems
Soldovieri F;
2020
Abstract
The present contribution deals with a reconstruction approach to the inverse electromagnetic scattering problem based on the joint exploitation of the deterministic linear inversion and global optimization strategies. The deterministic approach is based on the Born iterative method (BIM) enhanced by regularization techniques, such as Algebraic Reconstruction Technique (ART) and Conjugate Gradient (CG). In the second step of the overall strategy, a stochastic global optimization approach, the genetic algorithm (GA), is carried out. In this way, we will benefit from the regularization schemes and address the local minima problem. Numerical results are presented with reference to the permittivity reconstructions in the case of a homogeneous cylinder and an inhomogeneous layered cylinder.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
