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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Veröffentlicht in:IEEE transactions on antennas and propagation Jg. 57; H. 1; S. 280 - 283
Hauptverfasser: Rocca, P., Manica, L., Azaro, R., Massa, A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.01.2009
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
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
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2008.2009776