scholarly journals Subarrayed Antenna Array Synthesis Using Ternary Adjusting Method

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Guolong He ◽  
Yafeng Zhan ◽  
Yukui Pei ◽  
Bin Wu
Keyword(s):  
Particle Swarm Optimization ◽  
Antenna Array ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Element Number ◽  
Antenna Array Synthesis ◽  
Ternary Variables ◽  
Equation Constraint

Ternary adjusting method is proposed and combined with particle swarm optimization (PSO) algorithm for subarrayed antenna array synthesis. Ternary variables are introduced to represent element adjustments between adjacent subarrays. Compared to previous methods, rounding-off operations are not required any longer, and the equation constraint of the fixed total element number is also removed, which effectively reduces the complexity of implementation while obtaining improved topology exploration capability simultaneously.

scholarly journals Antenna optimization using Particle Swarm Optimization algorithm

2006 ◽  
Vol 16 (1) ◽  
pp. 21-24 ◽  
Author(s):  
Ruzica Golubovic ◽  
Dragan Olcan
Keyword(s):  
Particle Swarm Optimization ◽  
Antenna Array ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Yagi Antenna ◽  
Forward Gain

We present the results for two different antenna optimization problems that are found using the Particle Swarm Optimization (PSO) algorithm. The first problem is finding the maximal forward gain of a Yagi antenna. The second problem is finding the optimal feeding of a broadside antenna array. The optimization problems have 6 and 20 optimization variables, respectively. The preferred values of the parameters of the PSO algorithm are found for presented problems. The results show that the preferred parameters of PSO are somewhat different for optimization problems with different number of dimensions of the optimization space. The results that are found using the PSO algorithm are compared with the results that are found using other optimization algorithms, in order to estimate the efficiency of the PSO.

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