### 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.

Language | English (US) |
---|---|

Pages | 437-442 |

Number of pages | 6 |

Journal | Journal of Shanghai Jiaotong University (Science) |

Volume | 20 |

Issue number | 4 |

DOIs | |

State | Published - Aug 3 2015 |

Externally published | Yes |

### Fingerprint

### Keywords

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

### ASJC Scopus subject areas

- General

### Cite this

*Journal of Shanghai Jiaotong University (Science)*,

*20*(4), 437-442. DOI: 10.1007/s12204-015-1645-4

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

Research output: Contribution to journal › Article

*Journal of Shanghai Jiaotong University (Science)*, vol 20, no. 4, pp. 437-442. DOI: 10.1007/s12204-015-1645-4

}

TY - JOUR

T1 - Large thinned array design based on multi-objective cross entropy algorithm

AU - Bian,Li

AU - Bian,Chen yuan

AU - Wang,Shu min

PY - 2015/8/3

Y1 - 2015/8/3

N2 - 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.

AB - 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.

KW - cross entropy (CE) algorithm

KW - multi-objective optimization

KW - particle swarm optimization (PSO) algorithm

KW - thinned array

UR - http://www.scopus.com/inward/record.url?scp=84938381976&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84938381976&partnerID=8YFLogxK

U2 - 10.1007/s12204-015-1645-4

DO - 10.1007/s12204-015-1645-4

M3 - Article

VL - 20

SP - 437

EP - 442

JO - Journal of Shanghai Jiaotong University (Science)

T2 - Journal of Shanghai Jiaotong University (Science)

JF - Journal of Shanghai Jiaotong University (Science)

SN - 1007-1172

IS - 4

ER -