Comparing different approaches to linear antenna synthesis problems according to power radiation pattern

2014 ◽  
Author(s):  
Mykhaylo I. Andriychuk ◽  
Olena O. Bulatsyk ◽  
Nikolai N. Voitovich
Keyword(s):  
Radiation Pattern ◽  
Linear Antenna ◽  
Antenna Synthesis ◽  
Power Radiation

SYNTHESIS OF UNIFORM LINEAR ANTENNA ARRAY USING GENETIC ALGORITHM WITH COST BASED ROULETTE TO MAXIMIZE SIDELOBE LEVEL REDUCTION

2011 ◽  
Vol 08 (02) ◽  
pp. 171-179
Author(s):  
T. S. JEYALI LASEETHA ◽  
R. SUKANESH
Keyword(s):  
Genetic Algorithm ◽  
Antenna Array ◽  
Radiation Pattern ◽  
Optimization Method ◽  
Adaptive Beamforming ◽  
Linear Antenna ◽  
Algorithm Optimization ◽  
Sidelobe Level ◽  
Linear Antenna Array ◽  
Sidelobe Level Reduction

This paper discusses the deployment of Genetic Algorithm optimization method for the synthesis of antenna array radiation pattern in adaptive beamforming. The synthesis problem discussed is to find the weights of the Uniform Linear Antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the sidelobe level. This technique proved its effectiveness in improving the performance of the antenna array.

A Comparison of Swarm-Based Optimization Algorithms in Linear Antenna Array Synthesis

2021 ◽  
Author(s):  
Ali Durmus ◽  
Rifat KURBAN ◽  
Ercan KARAKOSE
Keyword(s):  
Antenna Array ◽  
Radiation Pattern ◽  
Antenna Arrays ◽  
Heuristic Algorithms ◽  
Beam Width ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Half Power ◽  
Antenna Array Synthesis

Abstract Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with low side lobe level (SLL) at a desired half power beam width (HPBW) in far-field. The amplitude and position values ​​of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper swarm-based meta-heuristic algorithms such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Mayfly algorithm (MA) and Jellyfish Search (JS) algorithms are compared to realize optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10, 16, 24 and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers and statistical results show that performance of the novel algorithms, MA and JS, are better than well-known methods PSO and ABC.

scholarly journals LINEAR ANTENNA SYNTHESIS WITH A HYBRID GENETIC ALGORITHM

2004 ◽  
Vol 49 ◽  
pp. 1-22 ◽  
Author(s):  
Massimo Donelli ◽  
Salvatore Caorsi ◽  
Francesco DeNatale ◽  
Matteo Pastorino ◽  
Andrea Massa
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Linear Antenna ◽  
Antenna Synthesis
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