Microwave Imaging 3-D Buried Objects Using Parallel Genetic Algorithm Combined With FDTD Technique

A microwave imaging technique based on the parallel genetic algorithm (PGA) and the finite-difference time-domain (FDTD) method is proposed in this paper for estimating the locations, dimensions and dielectric permittivity distributions of three-dimensional (3-D) objects buried in the lossy earth. The GA, a robust stochastic optimization procedure, is employed to recast the microwave imaging problem, an inverse scattering problem, to be a global nonlinear optimization problem and solve it. To reduce its heavy computation burden, the GA-based inverse computation is parallelized and run on a cluster system. A 3-D FDTD method with perfectly matched layer (PML) absorbing boundary condition (ABC) is selected for the forward calculation of the scattered field by the buried object. Sample numerical results are presented and analyzed. The analysis of the numerical results shows that the proposed microwave imaging technique based on the PGA and FDTD is able to recover the locations, dimensions and permittivity parameters of 3-D buried objects, and the parallel computation can sharply reduce the required computation time.

[1]  Eric Michielssen,et al.  Genetic algorithm optimization applied to electromagnetics: a review , 1997 .

[2]  Chak-Kuen Wong,et al.  A parallelized genetic algorithm for the calibration of Lowry model , 2001, Parallel Comput..

[3]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[4]  A. Massa,et al.  A new methodology based on an iterative multiscaling for microwave imaging , 2003 .

[5]  Jin Au Kong,et al.  Finite-difference time-domain simulation of scattering from objects in continuous random media , 2002, IEEE Trans. Geosci. Remote. Sens..

[6]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[7]  Matteo Pastorino,et al.  A microwave inverse scattering technique for image reconstruction based on a genetic algorithm , 2000, IEEE Trans. Instrum. Meas..

[8]  Anyong Qing,et al.  Microwave Imaging of Parallel Perfectly Conducting Cylinders Using Real-Coded Genetic Algorithm Coupled With Newton-Kantorivitch Method - Abstract , 2000 .

[9]  Matteo Pastorino,et al.  Microwave imaging within the second-order Born approximation: stochastic optimization by a genetic algorithm , 2001 .

[10]  Andrea Massa,et al.  Detection of buried inhomogeneous elliptic cylinders by a memetic algorithm , 2003 .

[11]  Siyuan Chen,et al.  Inverse scattering of two-dimensional dielectric objects buried in a lossy earth using the distorted Born iterative method , 2001, IEEE Trans. Geosci. Remote. Sens..

[12]  C. Chiu,et al.  Electromagnetic imaging for an imperfectly conducting cylinder by the genetic algorithm [medical application] , 2000 .

[13]  Chien-Ching Chiu,et al.  Frequency dependence on image reconstruction for a buried conductor , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[14]  Matteo Pastorino,et al.  Numerical assessment concerning a focused microwave diagnostic method for medical applications , 2000 .

[15]  Matteo Pastorino,et al.  Two-dimensional microwave imaging approach based on a genetic algorithm , 2000 .

[16]  R. Mittra,et al.  Detection of buried dielectric cavities using the finite-difference time-domain method in conjunction with signal processing techniques , 2000 .

[17]  Matteo Pastorino,et al.  A computational technique based on a real-coded genetic algorithm for microwave imaging purposes , 2000, IEEE Trans. Geosci. Remote. Sens..

[18]  C. Chiu,et al.  Inverse scattering of a buried imperfect conductor , 2000, DIPED - 2000. Proceedings of 5th International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (IEEE Cat. No.00TH8508).

[19]  Lawrence Carin,et al.  Time-domain sensing of targets buried under a rough air-ground interface , 1998, Defense, Security, and Sensing.

[20]  Weng Cho Chew,et al.  Novel diffraction tomographic algorithm for imaging two-dimensional targets buried under a lossy Earth , 2000, IEEE Trans. Geosci. Remote. Sens..

[21]  A New Noninvasive Method for Determining the Conductivity of Tissue Embedded in Multilayer Biological Structure , 2002 .

[22]  K. Yee.  Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media , 1966 .

[23]  Anyong Qing,et al.  Microwave Imaging of Parallel Perfectly Conducting Cylinders Using Real-Coded Genetic Algorithm Coupled with Newton-Kantorivitch Method , 2000 .

[24]  Ju-Jang Lee,et al.  Balancing the selection pressures and migration schemes in parallel genetic algorithms for planning multiple paths , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[25]  R. Luebbers,et al.  The Finite Difference Time Domain Method for Electromagnetics , 1993 .