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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Bibliographic Details
Published in:Shanghai jiao tong da xue xue bao 2015-08, Vol.20 (4), p.437-442
Main Author: 边莉 边晨源 王书民
Format: Article
Language:English
Subjects:
Algorithms
Antenna arrays
Architecture
Arrays
Computer Science
Electrical Engineering
Engineering
Entropy
Life Sciences
Materials Science
Noise levels
Optimization
Sidelobes
Swarm intelligence
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Summary: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.
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-015-1645-4