Synthesis of Uniformly Excited Time Modulated Unequally Spaced Linear Antenna Arrays Using Firefly Algorithm (FA)

Author(s):  
Mukesh Kumar ◽  
Bharath Raja Nenavath ◽  
S.K. Mandal
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).


Author(s):  
Hemant Patidar ◽  
Gautam Kumar Mahanti ◽  
Ramalingam Muralidharan

This paper deals with the synthesis of flattop and cosecant squared beam patterns using the firefly algorithm which is based on metaheuristics. This synthesis is followed by the correction of the radiation patterns when unfortunate malfunctioning of the individual elements in the array occurs. The necessary attention is given to the recovery process, with due emphasis on reduction of side lobe level, ripple and the reflection coefficient. Simulation in Matlab shows a successful employment of the firefly algorithm in producing voltage excitations of the good elements necessary for the recovered patterns. The performance of the firefly algorithm in failure correction is validated by duly comparing it with a standard benchmark.


2013 ◽  
Vol 6 (2) ◽  
pp. 181-194 ◽  
Author(s):  
Gopi Ram ◽  
Durbadal Mandal ◽  
Rajib Kar ◽  
Sakti Prasad Ghoshal

In this paper, an optimized hyper beamforming method is presented based on a hyper beam exponent parameter for receiving linear antenna arrays using a new meta-heuristic search method based on the Firefly algorithm (FFA). A hyper beam is derived from the sum and difference beam patterns of the array, each raised to the power of a hyper beam exponent parameter. As compared to the conventional hyper beamforming of the linear antenna array, FFA applied to the hyper beam of the same array can achieve much more reduction in sidelobe level (SLL) and improved first null beam width (FNBW), keeping the same value of the hyper beam exponent. As compared to the uniformly excited linear antenna array with inter-element spacing of λ/2, conventional non-optimized hyper beamforming and optimal hyper beamforming of the same obtained by real-coded genetic algorithm, particle swarm optimization and Differential evolution, FFA applied to the hyper beam of the same array can achieve much greater reduction in SLL and same or less FNBW, keeping the same value of the hyper beam exponent parameter. The whole experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.


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

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