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When particle swarm optimization (PSO) technique is used for the inverse scattering problems it will take unbearably long time for the flnal solution, especially when the PSO algorithm traps into the premature convergence. To overcome this problem a hybrid multi-phased particle swarm optimization algorithm (HMPPSO) is proposed. By adopting the small swarm size strategy and the idea of \sub swarms" working cooperatively and alternatively with \optimal swarm" into the MPPSO, the HMPPSO can converge quickly with much less fltness function evaluation times, thus will reduce the reconstruction time. After the HMPPSO is validated by the numerical simulations on benchmark functions, the wall parameters (permittivity, conductivity, and thickness) together with target shape parameters (approximated by the trigonometric serials) with 20dB additive Gaussian white noise are successfully reconstructed by HMPPSO using multi-frequency, multiview/singleillumination scattering flelds calculated by MOM.

HYBRID MULTI-PHASED PARTICLE SWARM OPTIMIZATION FOR THROUGH-WALL SHAPE RECONSTRUCTION AND WALL PARAMETERS ESTIMATION