Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm

doi:10.1007/s12204-015-1645-4

上海交通大学学报（英文版） ›› 2015, Vol. 20 ›› Issue (4): 437-442.doi: 10.1007/s12204-015-1645-4

Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm

BIAN Li1* (边莉), BIAN Chen-yuan1 (边晨源), WANG Shu-min2 (王书民)

(1. School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China; 2. Department of Electrical and Computer Engineering, Auburn University, Auburn 36849, USA)

发布日期:2015-08-05
通讯作者: BIAN Li (边莉) E-mail:branran@163.com

Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm

BIAN Li1* (边莉), BIAN Chen-yuan1 (边晨源), WANG Shu-min2 (王书民)

(1. School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China; 2. Department of Electrical and Computer Engineering, Auburn University, Auburn 36849, USA)

Published:2015-08-05
Contact: BIAN Li (边莉) E-mail:branran@163.com

摘要/Abstract

摘要： 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.

关键词: cross entropy (CE) algorithm, particle swarm optimization (PSO) algorithm, thinned array, multi-objective optimization

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.

Key words: thinned array, multi-objective optimization, cross entropy (CE) algorithm, particle swarm optimization (PSO) algorithm

中图分类号:

TN 82

BIAN Li1* (边莉), BIAN Chen-yuan1 (边晨源), WANG Shu-min2 (王书民). Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm[J]. 上海交通大学学报（英文版）, 2015, 20(4): 437-442.

BIAN Li1* (边莉), BIAN Chen-yuan1 (边晨源), WANG Shu-min2 (王书民). Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(4): 437-442.

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Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm

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