Improvement of Radiation Pattern for Linear Antenna Arrays Using Genetic Algorithm

Author(s):  
D. Mandal ◽  
S.K. Ghoshal ◽  
S. Das ◽  
S. Bhattacharjee ◽  
A.K. Bhattacharjee
Author(s):  
Bhargav Appasani ◽  
Rahul Pelluri ◽  
Vijay Kumar Verma ◽  
Nisha Gupta

Genetic Algorithm (GA) is a widely used optimization technique with multitudinous applications. Improving the performance of the GA would further augment its functionality. This paper presents a Crossover Improved GA (CIGA) that emulates the motion of fireflies employed in the Firefly Algorithm (FA). By employing this mimicked crossover operation, the overall performance of the GA is greatly enhanced. The CIGA is tested on 14 benchmark functions conjointly with the other existing optimization techniques to establish its superiority. Finally, the CIGA is applied to the practical optimization problem of synthesizing non-uniform linear antenna arrays with low side lobe levels (SLL) and low beam width, both requirements being incompatible. However, the proposed CIGA applied for the synthesis of a 12 element array yields an SLL of [Formula: see text]29.2[Formula: see text]dB and a reduced beam width of 19.1[Formula: see text].


2016 ◽  
Vol 10 (4) ◽  
pp. 442-452 ◽  
Author(s):  
Edson R. Schlosser ◽  
Marcos V.T. Heckler ◽  
Renato Machado ◽  
Alexis Fabricio Tinoco Salazar

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