Shape Reconstruction of a Perfectly Conducting Scatterer Using Differential Evolution and Particle Swarm Optimization

摘要: The shape reconstruction of a perfectly conducting 2-D scatterer by inverting transverse magnetic scattered field measurements is investigated. based on evolutionary algorithms that minimize the discrepancy between measured and estimated data. A closed cubic B-spline expansion adopted to represent contour. Two have been examined differential-evolution (DE) algorithm particle swarm optimization (PSO). Numerical results indicate DE outperforms PSO in terms accuracy convergence speed. Both techniques tested case simulated contaminated additive white Gaussian noise.