Synthesis of clustered linear arrays through a total variation compressive sensing approach

Abstract : In this work the problem of synthesizing the excitations of a linear array, clustered into contiguous sub-arrays of irregular length, is addressed. By suitably exploiting the behavior of clustered array aperture distributions (i.e., step-wise discrete functions), the problem has been formulated as the minimization of the total variation (TV) of the excitations, satisfying a matching condition on a predefined reference pattern. In virtue of the sparse nature of the unknowns, the minimization problem has been solved by means of an efficient total variation compressive sensing (TV-CS) optimization approach. A simple example validating the proposed technique is finally reported.
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Communication dans un congrès
11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.862-864, 2017, 〈10.23919/EuCAP.2017.7928540〉
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https://hal.archives-ouvertes.fr/hal-01583437
Contributeur : Andrea Massa <>
Soumis le : jeudi 7 septembre 2017 - 12:03:44
Dernière modification le : jeudi 26 avril 2018 - 17:21:52

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Anselmi Nicola, Giacomo Oliveri, Andrea Massa. Synthesis of clustered linear arrays through a total variation compressive sensing approach. 11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.862-864, 2017, 〈10.23919/EuCAP.2017.7928540〉. 〈hal-01583437〉

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