A Quantized Invasive Weed Optimization Based Antenna Array Synthesis with Digital Phase Control

被引:0
作者
Majumdar, Ratul [1 ]
Ghosh, Ankur [1 ]
Raha, Souvik [1 ]
Laha, Koushik [1 ]
Das, Swagatam [1 ]
机构
[1] Jadavpur Univ, Dept Elect & Telecommun Engg, Kolkata 700032, India
来源
SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT I | 2011年 / 7076卷
关键词
PARTICLE SWARM OPTIMIZATION; ALGORITHM; PATTERN; BINARY;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The design of antenna arrays aims at minimizing side-lobe levels far as practicable. So a major concern of designer is to optimize the side lobes to increase directivity, gain, and efficiency. Invasive Weed Optimization (IWO) is a recently developed, ecologically inspired metaheuristic algorithm that has already found some major applications in electromagnetic research. In this article the synthesis of array antenna pattern by digital phase shifters is accomplished with a modified version of the IWO algorithm called QIWO (Quantized Invasive Weed Optimization. The proposed algorithm searches for optimal solution of the fitness function, which contains the SLL value and the interference suppression keeping the main beam unchanged. The results obtained from this algorithm are better than that of QPSO (Quantized Particle Swarm Optimization) and BPSO (Binary Particle Swarm Optimization). In this paper the array factor is expressed mathematically by a linear transform, which is similar to Discrete Cosine Transform (DCT). This proposed algorithm is also found to be efficient in computing for large arrays.
引用
收藏
页码:102 / 109
页数:8
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