Large thinned array design based on multi-objective cross entropy algorithm

Li Bian, Chen yuan Bian, Shu min Wang

Research output: Research - peer-reviewArticle

  • 2 Citations

Abstract

To consider multi-objective optimization problem with the number of feed array elements and sidelobe level of large antenna array, multi-objective cross entropy (CE) algorithm is proposed by combining fuzzy c-mean clustering algorithm with traditional cross entropy algorithm, and specific program flow of the algorithm is given. Using the algorithm, large thinned array (200 elements) given sidelobe level (−10, −19 and −30 dB) problem is solved successfully. Compared with the traditional statistical algorithms, the optimization results of the algorithm validate that the number of feed array elements reduces by 51%, 11% and 6% respectively. In addition, compared with the particle swarm optimization (PSO) algorithm, the number of feed array elements from the algorithm is more similar, but the algorithm is more efficient.

LanguageEnglish (US)
Pages437-442
Number of pages6
JournalJournal of Shanghai Jiaotong University (Science)
Volume20
Issue number4
DOIs
StatePublished - Aug 3 2015
Externally publishedYes

Fingerprint

Entropy
Antenna feeders
Multiobjective optimization
Antenna arrays
Clustering algorithms
Particle swarm optimization (PSO)

Keywords

  • cross entropy (CE) algorithm
  • multi-objective optimization
  • particle swarm optimization (PSO) algorithm
  • thinned array

ASJC Scopus subject areas

  • General

Cite this

Large thinned array design based on multi-objective cross entropy algorithm. / Bian, Li; Bian, Chen yuan; Wang, Shu min.

In: Journal of Shanghai Jiaotong University (Science), Vol. 20, No. 4, 03.08.2015, p. 437-442.

Research output: Research - peer-reviewArticle

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