Microstrip-patch array design using a multiobjective GA

Microstrip-patch array design using a multiobjective GA

A Pareto multiobjective genetic algorithm (MOGA) has been applied to optimize the radiation characteristics of a 4/spl times/4 array of parasitically loaded microstrip-patch antennas in terms of sidelobe level (SLL), main-lobe half-power beamwidth, and dynamic range (DR). The geometry of the array c...

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Veröffentlicht in:IEEE antennas and wireless propagation letters 2005, Vol.4, p.100-103
Hauptverfasser: van Coevorden, C.M.D.J., Garcia, S.G., Pantoja, M.F., Bretones, A.R., Martin, R.G.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithm design and analysis
Antenna arrays
Antennas
Arrays
Bandwidth
Design optimization
Dynamic range
Feeding
Genetic algorithms
Genetic algorithms (GAs)
Geometry
Microstrip antenna arrays
Microstrip antennas
Pareto genetic algorithms
Pareto optimality
Pareto optimization
Sidelobes
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Beschreibung
Zusammenfassung:A Pareto multiobjective genetic algorithm (MOGA) has been applied to optimize the radiation characteristics of a 4/spl times/4 array of parasitically loaded microstrip-patch antennas in terms of sidelobe level (SLL), main-lobe half-power beamwidth, and dynamic range (DR). The geometry of the array configuration is fixed and the genetic algorithm (GA) finds the complex feeding coefficients of each element in the array.
ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2005.845907