Electromagnetic imaging of penetrable configurations by means of a GA/CG method

Caorsi, S.; Massa, Andrea; Pastorino, Matteo

doi:10.1016/j.measurement.2004.09.005

Cited by 1 publication

(1 citation statement)

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“…To overcome this drawback in local optimization algorithms, one solution is to perform a global search over the entire unknown domain of the inverse-scattering problem. Depending on the object properties and the formation of microwave imaging system, appropriate global multi-agent optimization methods, such as the genetic algorithm (GA) [8], particle swarm optimization PSO [9], and differntial evolution (DE) [10], single-agent techniques such as simulated annealing method [11], and hybrid algorithms such as GA/CG method [12], memetic algorithm [13], [14], and hybrid DE [15] have been applied to solve the inversescattering problem. While these meta-heuristics have acceptable performance for small numbers of unknowns, they do not usually scale well with complexity.…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Imaging of Dielectric Objects Using a Multidirectional-Search-Based Simulated Annealing

Etminan

Moghaddam

2018

IEEE J. Multiscale Multiphys. Comput. Tech.

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In this paper, we introduce a global optimization method that is a novel combination of the simulated annealing method and the multi-directional search algorithm. We demonstrate the use of the algorithm for a microwave-imaging system to obtain the electrical properties of objects. The proposed global optimizer significantly improves the performance and speed of the simulated annealing method by utilizing a nonlinear simplex search, starting from an initial guess, and taking effective steps in obtaining the global solution of the minimization problem. Due to the efficient performance of the proposed global optimization method, we are able to obtain the shape, location, and material properties of the target without considering any a priori information about them. The accuracy and applicability of the proposed imaging method is demonstrated with some numerical results in which two-dimensional images of multiple objects are successfully reconstructed. Based on the optimization techniques utilized in the inverse-scattering problems, microwave imaging methods could be classified as two major groups, namely, local and global optimization methods. Due to the substantially higher speed of convergence in local optimization algorithms [1], they have been more popular in solving the inverse problsms. Born iterative method, for example, is widely used as an effective imaging method to obtain

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