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Optimum design of both linear and planar sparse arrays with sidelobe level reduction using salp swarm algorithm

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  • Zailei Luo
  • Feng Liu
  • Zhibin Zou
  • Shaojun Guo
  • Tongsheng Shen

Abstract

Sparse arrays play an important role in the widely used acoustic and electromagnetic applications such as sonar, radar, and satellite. In this paper, a recently proposed swarm intelligence algorithm, salp swarm algorithm (SSA), is introduced for design of both linear and planar sparse antenna arrays with optimum sidelobe level (SLL). The design of sparse antenna arrays can be regarded as a nonlinear optimization problem, which the main optimization goal is finding optimum excitations and positions for antenna elements to achieve antenna array beam pattern with desired SLL. The SSA is a new kind of swarm intelligence algorithm which inspired by the swarming behavior of salps. Compared to other evolutionary algorithms, the SSA requires few algorithm-specified tuning parameters, which makes it simple and easy to use for engineering. Illustrative examples of both linear and planar arrays are given to verify the validity of the SSA for SLL reduction of sparse arrays.

Suggested Citation

  • Zailei Luo & Feng Liu & Zhibin Zou & Shaojun Guo & Tongsheng Shen, 2021. "Optimum design of both linear and planar sparse arrays with sidelobe level reduction using salp swarm algorithm," Journal of Electromagnetic Waves and Applications, Taylor & Francis Journals, vol. 35(5), pages 690-704, March.
    • Handle: RePEc:taf:tewaxx:v:35:y:2021:i:5:p:690-704
    DOI: 10.1080/09205071.2020.1855259
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