An innovative method for the synthesis of maximally sparse linear arrays matching arbitrary reference patterns is proposed. In the framework of sparseness constrained optimization, the approach exploits the multi-task Bayesian compressive sensing theory to enable the design of complex nonHermitian layouts with arbitrary radiation and geometrical constraints. By casting the pattern matching problem into a probabilistic formulation, a Relevance-Vector-Machine technique is used as solution tool. The numerical assessment points out the advances of the proposed implementation over the extension to complex patterns of [18] and it gives some indications about the reliability, flexibility, and numerical efficiency of the approach also in comparison with state-of-the-art sparse-arrays synthesis methods.
Complex-Weight Sparse Linear Array Synthesis by Bayesian Compressive Sampling / Oliveri, Giacomo; Carlin, Matteo; Massa, Andrea. - In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. - ISSN 0018-926X. - 60:5(2012), pp. 2309-2326.
Titolo: | Complex-Weight Sparse Linear Array Synthesis by Bayesian Compressive Sampling |
Autori: | Oliveri, Giacomo; Carlin, Matteo; Massa, Andrea |
Autori Unitn: | |
Titolo del periodico: | IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION |
Anno di pubblicazione: | 2012 |
Numero e parte del fascicolo: | 5 |
Codice identificativo Scopus: | 2-s2.0-84860696886 |
Codice identificativo ISI: | WOS:000303995900019 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/TAP.2012.2189742 |
Handle: | http://hdl.handle.net/11572/91642 |
Citazione: | Complex-Weight Sparse Linear Array Synthesis by Bayesian Compressive Sampling / Oliveri, Giacomo; Carlin, Matteo; Massa, Andrea. - In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. - ISSN 0018-926X. - 60:5(2012), pp. 2309-2326. |
Appare nelle tipologie: | 03.1 Articolo su rivista (Journal article) |
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