A Hybrid Approach to the Synthesis of Subarrayed Monopulse Linear Arrays

In this paper, a hybrid approach for the synthesis of the ldquooptimalrdquo compromise between sum and difference patterns for subarrayed monopulse antennas is presented. First, the subarray configuration is determined by exploiting the knowledge of the optimum difference mode coefficients to reduce...

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Podrobná bibliografia
Vydané v:	IEEE transactions on antennas and propagation Ročník 57; číslo 1; s. 280 - 283
Hlavní autori:	Rocca, P., Manica, L., Azaro, R., Massa, A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY IEEE 01.01.2009 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Antenna radiation patterns Antennas Applied sciences Complexity theory Contiguous partition convex programming Electromagnetic interference Electromagnetic radiation Electromagnetic radiative interference Exact sciences and technology Functional programming hybrid optimization Linear antenna arrays Linear arrays Linear programming Monopulse antennas Optimization Programming Radiocommunications Searching Signal synthesis Simulated annealing State of the art sum and difference patterns synthesis Synthesis Telecommunications Telecommunications and information theory Performance evaluation Automatic classification State of the art sum and difference patterns synthesis Signal classification Convex programming Optimization Contiguous partition hybrid optimization Hybrid model Convexity Linear antenna arrays Pattern synthesis
ISSN:	0018-926X, 1558-2221
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Popis
Shrnutí:	In this paper, a hybrid approach for the synthesis of the ldquooptimalrdquo compromise between sum and difference patterns for subarrayed monopulse antennas is presented. First, the subarray configuration is determined by exploiting the knowledge of the optimum difference mode coefficients to reduce the dimension of the searching space. In the second step, the subarray weights are computed by means of a convex programming procedure, which takes advantages from the convexity, for a fixed clustering, of the problem at hand. A set of representative results is reported to assess the effectiveness of the proposed approach. Comparisons with state-of-the-art techniques are also presented.
Bibliografia:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 content type line 23
ISSN:	0018-926X 1558-2221
DOI:	10.1109/TAP.2008.2009776