Automated dual band patch antenna design by a genetic algorithm based numerical code

Castellana, Francesco; Bilotti, Filiberto; Vegni, Lucio

doi:10.1109/aps.2001.959561

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…As discussed previously, the goal here is to develop a method for generation an optimal or near optimal antenna structure. The approach that is adopted in the GA/MOM is to begin with a mother structure through an iterative GA [10][11][12][13][14] search with MoM as a basic analytical method.…”

Section: Ga/mom Integrationmentioning

confidence: 99%

Genetic Algorithms and Method of Moments for the Design of Pifas

Su¹,

Demin²,

Yu³

2008

PIER Letters

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This paper presents a novel technique for efficiently combining genetic algorithms (GA's) with method of moments (MOM) for planar inverted-F antennas (PIFAs). MOM is applied to analyze rectangular patches fed by a coaxial probe and shorted with a shorted pin. The impedance matrix of such a mother structure is, then manipulated by a GA optimization procedure in order to detect the optimal patch shape matching the required frequency properties. GA adoption enables optimal shape detection among all possible shapes allowed by the mother structure dimensions. The design example of dual-band antenna is presented, and measurement result is compared to numerical results. Excellent agreement between numerical and measured results is observed.

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Section: Ga/mom Integrationmentioning

confidence: 99%

Genetic Algorithms and Method of Moments for the Design of Pifas

Su¹,

Demin²,

Yu³

2008

PIER Letters

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Particle swarm optimization for designing a micro strip patch antenna for Ku band applications

Singh¹,

Sappal

2015

2015 International Conference and Workshop on Computing and Communication (IEMCON)

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Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review

Jayasinghe

2021

ELECTRENG

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<abstract> <p>Researchers have proposed applying optimization techniques to improve performance of microstrip antennas (MSAs) in terms of bandwidth, radiation characteristics, polarization, directivity and size. The drawbacks of the conventional MSAs can be overcome by optimizing the antenna parameters while keeping a compact configuration. Applying a global optimizer is a better technique than using a local optimizer or a trial and error method for performance enhancement. This paper discusses genetic algorithm (GA) optimization of microstrip antennas presented by the antenna research community. The GA optimization procedure, antenna parameters optimized by using GA and the optimization objectives are presented by reviewing the literature. Further, evolution of GA in the field of MSAs and its significance are explored. Application of GA optimization to design broadband, multiband, high-directivity and miniature antennas is demonstrated with the support of several case studies giving an insight for further developments in the field.</p> </abstract>

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Automated dual band patch antenna design by a genetic algorithm based numerical code

Cited by 3 publications

References 3 publications

Genetic Algorithms and Method of Moments for the Design of Pifas

Genetic Algorithms and Method of Moments for the Design of Pifas

Particle swarm optimization for designing a micro strip patch antenna for Ku band applications

Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review

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