A large 3D target with small inner details: A difficult cocktail for imaging purposes without a priori knowledge on the scatterers geometry

Abstract

[1] To accurately image a complex shape but large 3D target whose scattered field has been measured in an anechoic environment at high frequencies (18 and 20 GHz), we have developed a complete imaging process, combining experimental and numerical works. The adopted strategy exploits the maximum of available information related to the measurements, both in terms of quantity and accuracy without any a priori knowledge on the scatterer geometry. We first determine the position and then the dimension of the spatial domain which contains the target. This localization is realized directly from the analysis of the spectrum of the measured fields taking into account the random noise disturbing the measurement points. Then, we construct a quantitative permittivity map of this investigation domain thanks to an iterative inversion procedure based on a Bayesian formulation where the spatial diversity of the real random noise is adequately exploited. By following this strategy, we have been able to quantitatively retrieve the target both in terms of dimension, shape and electromagnetic properties, even with a very limited number of measurement points and for a single polarization case. With such a process, even spheres with a diameter equal to l/3 are correctly reconstructed at 20 GHz.Citation: Eyraud, C., J.-M. Geffrin, A. Litman, and J.-P. Spinelli (2012), A large 3D target with small inner details: A difficult cocktail for imaging purposes without a priori knowledge on the scatterers geometry, Radio Sci., 47, RS0E23,

Buried object detection by means of a Lp Banach‐space inversion procedure

“…In this framework, new inversion strategies, ranging from radar-based approaches to inverse-scattering-based tomographic imaging methods, are continuously proposed in order to extend the diagnostic capabilities and to mitigate the drawbacks of existing techniques [Eyraud et al, 2012;Wang et al, 2013;Elbir and Tuncer, 2014;Jacobson et al, 2014;Kalkan and Baykal, 2014]. In the previous years, several advancements in imaging methods, especially for free-space configurations, have been reported in the scientific literature [Harding and Milla, 2013;Song and Liu, 2005;Micolau and Saillard, 2003;Solimene et al, 2013;Mohanna et al, 2013;Meschino et al, 2013;Zhang et al, 2011;Scapaticci et al, 2012;Poli et al, 2013;Agarwal et al, 2013;Heilpern et al, 2013;Gurbuz et al, 2014;Dagefu and Sarabandi, 2014;Laviada et al, 2014].…”

3-D Imaging of a Microwave Absorber Sample From Microwave Scattered Field Measurements

“…In this letter, the investigation zone is limited to the center of the spherical setup, but its position and size can directly be deduced from the measurements [8]. An iterative scheme is adopted to solve this inverse scattering problem.…”

“…To test the efficiency of our experimental [5], [7] and numerical developments [8] in a borderline case, we have selected a component that every microwave experimenter has been working with: the extremity of a microwave absorbing pyramid. With this target, we face major difficulties: it is a low scattering target, large with respect to the wavelength, eventually heterogeneous and with a finite loss tangent worth to be accurately determined.…”

Simplified two‐dimensional microwave imaging scheme using metamaterial‐loaded Vivaldi antenna

“…Some of the common microwave imaging applications reported in the past by the researchers are nondestructive testing [Akhtar, 2008;Kharkovsky and Zoughi, 2007], crack and moisture detection in concrete walls [Ghasr et al, 2006], reconstruction of permittivity profiles [Akhtar and Omar, 2000], cancer/tumor detection [Mehta et al, 2006], near-field tomography technique [Hossain and Mohan, 2015], and the far-field radar imaging techniques in wireless communications [Viani et al, 2011;Fouda et al, 2012;Wang et al, 2013]. Microwave imaging applications at high frequencies are also discussed where brightness temperature measurement is done at ocean surface [Bettenhausen and Adams, 2013] and the detection of 3-D targets using Bayesian formulation [Eyraud et al, 2012]. In addition, there are a number of other potential applications of microwave imaging which have not yet been fully explored.…”