A comparison of range test method-linear sampling method for microwave imaging

Range test method (RTM) is a qualitative imaging algorithm, which is based on analytic extensibility of the scattered electric field. Although detailed analysis of the RTM can be found in the mathematical literature, the method is not well-analyzed from an engineering perspective. In particular, the numerical performance of RTM is not compared with the other well-known shape reconstruction methods. In this direction, this paper present a numerical comparison of the RTM with the linear sampling method (LSM). To this aim, scattered electric fields for several configurations are produced synthetically via a 2D method of moments (MoM) code. After corrupting the scattered field data with a synthetic noise, the noisy fields are supplied to both LSM and RTM and binary shape reconstructions are obtained. Quality of the reconstruction results are evaluated with the well-known Jaccard index. Obtained reconstructions show that the RTM is also a promising qualitative approach for microwave imaging applications.

[1]  D. Colton,et al.  The linear sampling method in inverse electromagnetic scattering theory , 2003 .

[2]  Ibrahim Akduman,et al.  Qualitative Microwave Imaging With Scattering Parameters Measurements , 2015, IEEE Transactions on Microwave Theory and Techniques.

[3]  Ibrahim Akduman,et al.  An Efficient Nonlinear Imaging Approach for Dielectric Objects Buried Under a Rough Surface , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Eric L. Miller,et al.  Subsurface Sensing of Buried Objects Under a Randomly Rough Surface Using Scattered Electromagnetic Field Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Matteo Pastorino,et al.  Recent inversion procedures for microwave imaging in biomedical, subsurface detection and nondestructive evaluation applications , 2004 .

[6]  Roland Potthast,et al.  A multiwave range test for obstacle reconstructions with unknown physical properties , 2007 .

[7]  Zhou Wang,et al.  Complex Wavelet Structural Similarity: A New Image Similarity Index , 2009, IEEE Transactions on Image Processing.

[8]  N I Grinberg,et al.  The Factorization Method for Inverse Problems , 2007 .

[9]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[10]  P. Jaccard Distribution de la flore alpine dans le bassin des Dranses et dans quelques régions voisines , 1901 .

[11]  T. Isernia,et al.  On Simple Methods for Shape Reconstruction of Unknown Scatterers , 2007, IEEE Transactions on Antennas and Propagation.

[12]  Roger F. Harrington,et al.  Field computation by moment methods , 1968 .

[13]  Matteo Pastorino,et al.  A crack identification microwave procedure based on a genetic algorithm for nondestructive testing , 2001 .

[14]  Aria Abubakar,et al.  The contrast source inversion method for location and shape reconstructions , 2002 .

[16]  Roland Potthast,et al.  A 'range test' for determining scatterers with unknown physical properties , 2003 .

[17]  T. Isernia,et al.  Improved Sampling Methods for Shape Reconstruction of 3-D Buried Targets , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Mehmet Cayoren,et al.  Microwave Imaging of a Slightly Varying 2-D Conducting Object Through Generalized Impedance Boundary Conditions , 2014, IEEE Geoscience and Remote Sensing Letters.

[19]  R. Potthast,et al.  From the Kirsch-Kress potential method via the range test to the singular sources method , 2005 .

[20]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

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

[22]  Ugur Alkasi,et al.  Experimental Assessment of Linear Sampling and Factorization Methods for Microwave Imaging of Concealed Targets , 2015 .