A Diagonal Subspace-Based Optimization Method for Reconstruction of 2-D Isotropic and Uniaxial Anisotropic Dielectric Objects

In this letter, a diagonal approximation has been introduced in the framework of subspace-based optimization method (SOM), for reducing computational complexity. Due to this approximation, the operator which relates the electric field and equivalent current becomes a diagonal one, instead of the nonlinear one in full-wave inversion. Consequently, the proposed method is named as diagonal SOM (DSOM). Compared with the original SOM, DSOM has a more simplified objective function with much less computational cost. DSOM can be applied for solving inverse scattering problems involving not only isotropic objects, but also uniaxial anisotropic objects, which is demonstrated by numerical examples. Furthermore, DSOM provides reconstruction results that are comparable in quality to the ones obtained using SOM, but with much less computation load.

[1]  S.Y. Semenov,et al.  Microwave tomography: two-dimensional system for biological imaging , 1996, IEEE Transactions on Biomedical Engineering.

[2]  Andrea Massa,et al.  Multiresolution subspace-based optimization method for inverse scattering problems. , 2011, Journal of the Optical Society of America. A, Optics, image science, and vision.

[3]  Qing Huo Liu,et al.  Through-wall imaging (TWI) by radar: 2-D tomographic results and analyses , 2005, IEEE Trans. Geosci. Remote. Sens..

[4]  Tommaso Isernia,et al.  On the Solution of 2-D Inverse Scattering Problems via Source-Type Integral Equations , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[5]  J. Lovetri,et al.  Overview and Classification of Some Regularization Techniques for the Gauss-Newton Inversion Method Applied to Inverse Scattering Problems , 2009, IEEE Transactions on Antennas and Propagation.

[6]  P. M. Berg,et al.  A contrast source inversion method , 1997 .

[7]  Xudong Chen Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium , 2010 .

[8]  Xudong Chen,et al.  Subspace-Based Optimization Method for Reconstruction of 2-D Complex Anisotropic Dielectric Objects , 2010, IEEE Transactions on Microwave Theory and Techniques.

[9]  Ali Yapar,et al.  A Nonlinear Microwave Breast Cancer Imaging Approach Through Realistic Body–Breast Modeling , 2014, IEEE Transactions on Antennas and Propagation.

[10]  Andrea Massa,et al.  Multi-resolution subspace-based optimization method for solving three-dimensional inverse scattering problems. , 2015, Journal of the Optical Society of America. A, Optics, image science, and vision.

[11]  Amin M. Abbosh,et al.  Microwave imaging for brain stroke detection using Born iterative method , 2013 .

[12]  Xudong Chen,et al.  Improving the Performances of the Contrast Source Extended Born Inversion Method by Subspace Techniques , 2013, IEEE Geoscience and Remote Sensing Letters.

[13]  W. Chew,et al.  Reconstruction of two-dimensional permittivity distribution using the distorted Born iterative method. , 1990, IEEE transactions on medical imaging.

[14]  P. M. Berg,et al.  The diagonalized contrast source approach: an inversion method beyond the Born approximation , 2005 .