The power synthesis of maximally sparse arrays such to maximize the beam efficiency over a target region Ω is addressed. In particular, Ω is the unique input parameter of the proposed design procedure, and once it has been fixed, the approach allows identifying the minimum number of elements required to achieve inside it a beam efficiency close to the theoretical maximum. The problem is cast as a convex programming one that exploits at best the compressive sensing theory. Comparisons to state-of-the-art methods are provided.

Synthesis of Maximum-Efficiency Beam Arrays via Convex Programming and Compressive Sensing

A. F. Morabito
2017

Abstract

The power synthesis of maximally sparse arrays such to maximize the beam efficiency over a target region Ω is addressed. In particular, Ω is the unique input parameter of the proposed design procedure, and once it has been fixed, the approach allows identifying the minimum number of elements required to achieve inside it a beam efficiency close to the theoretical maximum. The problem is cast as a convex programming one that exploits at best the compressive sensing theory. Comparisons to state-of-the-art methods are provided.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/3298
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