Browsing by Author "D’Elia, G."

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    An effective approach to the fast, GPU-Based, Through-Wall imaging
    (Видавництво Національного університету "Львівська політехніка", 2009) Capozzoli, A.; Curcio, C.; D’Elia, G.; Iadarola, G.; Liseno, A.; Vinetti, P.
    We present an approach for the Through-Wall-Imaging based on a simple model of the scattering problem involving few unknowns, exploiting effectively the a priori information on the scenario and using a global optimization approach, relying on Legendre- Fenchel Transforms, tailored to fast, parallel implementations on Graphic Processing Units (GPUs). Experimental results are presented against X-band data collected in a realistic scenario made of a wall of Ytong concrete blocks and a metallic cylindrical scatterer.
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    An optimized MAS for solving scattering problems
    (Видавництво Національного університету "Львівська політехніка", 2009) Capozzoli, A.; Liseno, A.; Vinetti, P.; Curcio, C.; De Bono, G.; D’Elia, G.
    A new criterion driving the choice of the locations of the Auxiliary Sourcers (AS) is introduced with the aim to improve the performance of the Method of Auxiliary Sources (MAS) applied to the solution of the integral equations as those encountered in electromagnetic scattering. The approach is based on the optimization of the singular value behavior of the matrix relating the AS excitations and the scattered field values at the matching points on the scatterer boundary. The ill-conditioning of the problem of determining the AS excitations matching the boundary conditions is then significantly reduced and the accuracy of the estimated scattered field is improved. The performance of the method is numerically assessed, in a 2D scalar geometry, by discussing in the details the case of a circular perfectly conducting scatterer.
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    NUFFT-based imaging of vegetation on graphic cards
    (Видавництво Національного університету "Львівська політехніка", 2009) Capozzoli, A.; Curcio, C.; D’Elia, G.; Di Vico, A.; Liseno, A.; Vinetti, P.
    We present an algorithm for the fast tomography of vegetation, based on a Radon mathematical setting and on the combined use of advanced processing algorithms (Non-Uniform FFTs) and hardware resources (Graphic Processing Units - GPUs). The algorithm performance is firstly numerically estimated, showing the favorable trade off between faithfulness and speed, and highlighting the convenience of the GPU implementation against that on CPU. Experimental results on anechoic chamber data complete the algorithm assessment.