The paper presents the application of the hybrid global optimization algorithm, introduced in the companion paper Part I, to reflector antenna power pattern synthesis and reflector antenna surface diagnosis from only amplitude data. The synthesis algorithm determines both the reflector surface and the excitation coefficients of the array of primary feeds to meet the designing specification on the far-field pattern expressed by means of two couple of masks bounding the squared amplitude of both the copolar and crosspolar components. The diagnosis technique allows to find the reflector surface profile from the measurement of the far field power pattern by a proper formulation of the corresponding inverse problem. In both cases we take advantage of the exploring capability of an evolutionary algorithm and of the solution refinement capability of an efficient, quasi-Newton based, local search procedure. The numerical analysis shows that Global Optimization can outperform the standard local approach, by significantly improving the performance of the synthesized antenna in the first case and by enhancing the reliability of the diagnosis procedure in the second one.

Global optimization and antenna synthesis and diagnosis, part two: applications to advanced reflector antennas synthesis and diagnosis techniques

CAPOZZOLI, AMEDEO;D'ELIA, GIUSEPPE
2006

Abstract

The paper presents the application of the hybrid global optimization algorithm, introduced in the companion paper Part I, to reflector antenna power pattern synthesis and reflector antenna surface diagnosis from only amplitude data. The synthesis algorithm determines both the reflector surface and the excitation coefficients of the array of primary feeds to meet the designing specification on the far-field pattern expressed by means of two couple of masks bounding the squared amplitude of both the copolar and crosspolar components. The diagnosis technique allows to find the reflector surface profile from the measurement of the far field power pattern by a proper formulation of the corresponding inverse problem. In both cases we take advantage of the exploring capability of an evolutionary algorithm and of the solution refinement capability of an efficient, quasi-Newton based, local search procedure. The numerical analysis shows that Global Optimization can outperform the standard local approach, by significantly improving the performance of the synthesized antenna in the first case and by enhancing the reliability of the diagnosis procedure in the second one.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/101671
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