Optimal Design of Linear Antenna Arrays of Dipole Elements Using Flower Pollination Algorithm

2018 ◽  
Vol 65 (5) ◽  
pp. 694-701 ◽  
Author(s):  
Gopi Ram ◽  
Rajib Kar ◽  
Durbadal Mandal ◽  
Sakti Prasad Ghoshal
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Urvinder Singh ◽  
Rohit Salgotra

In this paper, a new variant of flower pollination algorithm (FPA), namely, enhanced flower pollination algorithm (EFPA), has been proposed for the pattern synthesis of nonuniform linear antenna arrays (LAA). The proposed algorithm uses the concept of Cauchy mutation in global pollination and enhanced local search to improve the exploration and exploitation tendencies of FPA. It also uses dynamic switching to control the rate of exploration and exploitation. The algorithm is tested on standard benchmark problems and has been compared statistically with state of the art to prove its worthiness. LAA design is a tricky and difficult electromagnetic problem. Hence to check the efficacy of the proposed algorithm it has been used for synthesis of four different LAA with different sizes. Experimental results show that EFPA algorithm provides enhanced performance in terms of side lobe suppression and null control compared to FPA and other popular algorithms.


2014 ◽  
Vol 34 ◽  
pp. 135-142 ◽  
Author(s):  
Sujit Kumar Mandal ◽  
Gautam Kumar Mahanti ◽  
Rowdra Ghatak

2014 ◽  
Vol 13 (7) ◽  
pp. 3791-3805 ◽  
Author(s):  
Peng Wang ◽  
Yonghui Li ◽  
Xiaojun Yuan ◽  
Lingyang Song ◽  
Branka Vucetic

Author(s):  
Anas A. Amaireh ◽  
Asem S. Al-Zoubi ◽  
Nihad I. Dib

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA).


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