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In this paper, the retrieval of sparse defects within known two-dimensional structures is addressed. A Bayesian Compressive Sensing technique has been developed to determine the differential induced currents thanks to a proper definition of an inhomogeneous Green's function enabled from the a-priori knowledge of the unperturbed structure. Successively, a contrast source inversion method has been applied...
This paper presents an innovative microwave imaging technique for detecting defects in dielectric or conductive media developed through the Bayesian Compressive Sensing theory. Thanks to the a-priori knowledge of the medium unaffected by defects, the inversion problem is formulated as the estimation of the sparse differential equivalent currents within the support of the defects. The strategy has...
In this paper, time-domain inverse-scattering technique referred to as Forward-Backward Time-Stepping (FBTS) method is applied to microwave imaging breast cancer detection. The FBTS algorithm is implemented in C++ language executed in a single computer by developing the time domain form of the FDTD. The ability to detect as small as 4mm of the embedded tumour and reconstructing the image in two-dimensional...
We consider cross-borehole imaging of buried objects embedded in a large search area by using a time domain inverse analysis. For simplicity, a two-dimensional model is examined. In order to avoid trap into false solution and enhance the achievable spatial resolution, the iterative multiscaling strategy combined with the forward-backward time-stepping method is proposed. Preliminary results show the...
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