Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm
In this paper, an improved genetic algorithm with dynamic weight vector (IGA-DWV) is proposed for the pattern synthesis of a linear array. To maintain the diversity of the selected solution in each generation, the objective function space is divided by the dynamic weight vector, which is uniformly d...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2019/1064103 |
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| author | Bo Yang |
| author_facet | Bo Yang |
| author_sort | Bo Yang |
| collection | DOAJ |
| description | In this paper, an improved genetic algorithm with dynamic weight vector (IGA-DWV) is proposed for the pattern synthesis of a linear array. To maintain the diversity of the selected solution in each generation, the objective function space is divided by the dynamic weight vector, which is uniformly distributed on the Pareto front (PF). The individuals closer to the dynamic weight vector can be chosen to the new population. Binary- and real-coded genetic algorithms (GAs) with a mapping method are implemented for different optimization problems. To reduce the computation complexity, the repeat calculation of the fitness function in each generation is replaced by a precomputed discrete cosine transform matrix. By transforming the array pattern synthesis into a multiobjective optimization problem, the conflict among the side lobe level (SLL), directivity, and nulls can be efficiently addressed. The proposed method is compared with real number particle swarm optimization (RNPSO) and quantized particle swarm optimization (QPSO) as applied in the pattern synthesis of a linear thinned array and a digital phased array. The numerical examples show that IGA-DWV can achieve a high performance with a lower SLL and more accurate nulls. |
| format | Article |
| id | doaj-art-788a0aa119cd472d87afd2baa8eedeaf |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-788a0aa119cd472d87afd2baa8eedeaf2025-02-03T01:01:33ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772019-01-01201910.1155/2019/10641031064103Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic AlgorithmBo Yang0School of Electronic Science and Engineering, Jilin University, 130012 Changchun, ChinaIn this paper, an improved genetic algorithm with dynamic weight vector (IGA-DWV) is proposed for the pattern synthesis of a linear array. To maintain the diversity of the selected solution in each generation, the objective function space is divided by the dynamic weight vector, which is uniformly distributed on the Pareto front (PF). The individuals closer to the dynamic weight vector can be chosen to the new population. Binary- and real-coded genetic algorithms (GAs) with a mapping method are implemented for different optimization problems. To reduce the computation complexity, the repeat calculation of the fitness function in each generation is replaced by a precomputed discrete cosine transform matrix. By transforming the array pattern synthesis into a multiobjective optimization problem, the conflict among the side lobe level (SLL), directivity, and nulls can be efficiently addressed. The proposed method is compared with real number particle swarm optimization (RNPSO) and quantized particle swarm optimization (QPSO) as applied in the pattern synthesis of a linear thinned array and a digital phased array. The numerical examples show that IGA-DWV can achieve a high performance with a lower SLL and more accurate nulls.http://dx.doi.org/10.1155/2019/1064103 |
| spellingShingle | Bo Yang Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm International Journal of Antennas and Propagation |
| title | Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm |
| title_full | Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm |
| title_fullStr | Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm |
| title_full_unstemmed | Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm |
| title_short | Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm |
| title_sort | multiobjective synthesis of linear arrays by using an improved genetic algorithm |
| url | http://dx.doi.org/10.1155/2019/1064103 |
| work_keys_str_mv | AT boyang multiobjectivesynthesisoflineararraysbyusinganimprovedgeneticalgorithm |