Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm
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 flo...
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| Published in | Shanghai jiao tong da xue xue bao Vol. 20; no. 4; pp. 437 - 442 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Shanghai
Shanghai Jiaotong University Press
01.08.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1007-1172 1995-8188 |
| DOI | 10.1007/s12204-015-1645-4 |
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| 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 d B） 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. |
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| AbstractList | 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 d B） 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. 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. 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. |
| Author | 边莉 边晨源 王书民 |
| AuthorAffiliation | School of Electronic and Information Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China Department of Electrical and Computer Engineering, Auburn University, Auburn 36849, USA |
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| CitedBy_id | crossref_primary_10_1109_MAP_2016_2630041 crossref_primary_10_1186_s13638_019_1547_5 |
| Cites_doi | 10.1109/LAWP.2006.880693 10.1016/S0377-2217(96)00385-2 10.1109/58.753023 10.1007/s10479-005-5730-1 10.2528/PIER07081501 10.1007/978-3-540-24854-5_20 10.1007/3-540-36970-8_1 10.1109/TAP.2007.891552 10.1109/TAP.1964.1138239 10.1109/8.596902 10.1109/TAP.1964.1138220 10.1109/4235.996017 10.1007/978-1-4757-0450-1 |
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| Keywords | TN 82 multi-objective optimization cross entropy (CE) algorithm particle swarm optimization (PSO) algorithm thinned array |
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| Notes | 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 d B） 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. 31-1943/U BIAN Li,BIAN Chen-yuan,WANG Shu-min（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） thinned array; multi-objective optimization; cross entropy（CE） algorithm; particle swarm optimization（PSO） algorithm ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| SubjectTerms | Algorithms Antenna arrays Architecture Arrays Computer Science Electrical Engineering Engineering Entropy Life Sciences Materials Science Noise levels Optimization Sidelobes Swarm intelligence |
| Title | Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm |
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