Comparison of particle swarm optimization and self-adaptive dynamic differential evolution for the imaging of a periodic conductor

Abstract

The application of two techniques to reconstruct the shape of a two-dimensional periodic perfect conductor from mimic the measurement data is presented. A periodic conducting cylinder of unknown periodic length and shape scatters the incident wave in half-space and the scattered field is recorded outside. After an integral formulation, the microwave imaging is recast as a nonlinear optimization problem; a cost functional is defined by the norm of a difference between the measured scattered electric fields and the calculated scattered fields for an estimated shape of a conductor. Thus, the shape of conductor can be obtained by minimizing the cost function. In order to solve this inverse scattering problem, transverse magnetic (TM) waves are incident upon the objects and two techniques are employed to solve these problems. The first is based on an particle swarm optimization (PSO) and the second is a self-adaptive dynamic differential evolution (SADDE). Both techniques have been tested in the case of simulated mimic the measurement data contaminated by additive white Gaussian noise. Numerical results indicate that the SADDE algorithm is better than the PSO in reconstructed accuracy and convergence speed.

Microwave imaging of periodic rough surfaces

“…SADDE has been widely used in antenna, filter and other electromagnetic optimization problems. Regarding microwave imaging, SADDE is better than DE, GA, and PSO . To the best of our knowledge, the reconstruction for the periodic rough surface has not been reported yet by SADDE.…”

“…Global search method can be divided into random and non‐random 2 categories. Randomized global search is a computational intelligence that optimized by evolutionary algorithms, such as genetic algorithms (GAs), differential evolution (DE), particle swarm optimization (PSO), self‐adaptive dynamic differential evolution (SADDE) . Evolutionary calculations have the following benefits: (1) Use ethnic search to prevent the algorithm falling into local extremes.…”

A Hybrid Algorithm Based on a Modified Sine Cosine Algorithm and Least Square and Its Application to Microwave Imaging

“…For instance, researchers [7][8][9][10] introduced particle swarm optimization (PSO) to solve the inverse scattering problems, and the results proved the feasibility of PSO. Researchers introduced the engineering application of PSO and differential evolution (DE) to reconstruct the shape of a perfect electrical conductor, human tissue, scatterer profile, and shape from the measurement data of the scattered field [11][12][13].…”