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

  • Li Bian (边 莉)Email author
  • Chen-yuan Bian (边晨源)
  • Shu-min Wang (王书民)


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.


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

CLC number

TN 82 


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Copyright information

© Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Li Bian (边 莉)
    • 1
    Email author
  • Chen-yuan Bian (边晨源)
    • 1
  • Shu-min Wang (王书民)
    • 2
  1. 1.School of Electronic and Information EngineeringHeilongjiang University of Science and TechnologyHarbinChina
  2. 2.Department of Electrical and Computer EngineeringAuburn UniversityAuburnUSA

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