Performance of Beamwidth Constrained Linear Array Synthesis Techniques Using Novel Evolutionary Computing Tools

Authors

  • Chowdary S.R. Paladuga Department of Electronics & Communication Engineering Raghu Institute of Technology, Visakhapatnam, India
  • Chakravarthy V.S.S.S. Vedula Department of Electronics & Communication Engineering Raghu Institute of Technology, Visakhapatnam, India
  • Jaume Anguera Department of Electronics and Telecommunications University Ramon Llull, Barcelona, Spain, Fractus Antennas, Barcelona, Spain
  • Rabindra K. Mishra Department of Electronics, Berhampur University Berhampur, Odisha, India
  • Aurora Andújar Department of Electronics and Telecommunications University Ramon Llull, Barcelona, Spain, Fractus Antennas, Barcelona, Spain,

Keywords:

Antenna optimization, array synthesis, flower pollination algorithm, particle swarm optimization

Abstract

Antenna array synthesis for desired radiation characteristics is a challenging field of research in electromagnetics. When an array synthesis problem is visualized as an optimization problem several design parameters involved in synthesis process are considered as degrees of freedom. Every combination of design parameters forms a synthesis technique. In this paper, certain emphasis is given to analyse the techniques of linear array (LA) design using evolutionary computing tools. Novel computing tools like Flower Pollination Algorithm is used for LA synthesis using different degrees of freedom and compared with a conventional Tchebycheff method. Accelerated Particle Swarm Optimization (APSO) is also employed to study the consistency of the technique with the employed computing tool. Radiation patterns are generated with optimized SLL and Tchebycheff beamwidth constraint.

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References

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Published

2021-07-25

How to Cite

[1]
Chowdary S.R. Paladuga, Chakravarthy V.S.S.S. Vedula, Jaume Anguera, Rabindra K. Mishra, and Aurora Andújar, “Performance of Beamwidth Constrained Linear Array Synthesis Techniques Using Novel Evolutionary Computing Tools”, ACES Journal, vol. 33, no. 03, pp. 273–278, Jul. 2021.

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