Side lobe pattern synthesis using hybrid SSWOA algorithm for conformal antenna array

Prabhakar, D.; Satyanarayana, M.

doi:10.1016/j.jestch.2019.06.009

Cited by 18 publications

(10 citation statements)

References 26 publications

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“…As far as the SSA [37] is concerned, various efforts in antenna design optimization are found in the literature. Prabhakar and Satyanarayana [77] combined the SSA and the WOA to propose a new hybrid algorithm in order to address the problem of pattern synthesis in a conformal antenna array. The proposed hybrid algorithm is evaluated through a series of several well-known test functions.…”

Section: Related Workmentioning

confidence: 99%

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

et al. 2021

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Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands.

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Section: Related Workmentioning

confidence: 99%

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

et al. 2021

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“…This technique is believed to have better gain and efficiency. Using the method of moments and finite element method to base the full-wave electromagnetic solvers, Alibakhshikenari, and Virdee have optimized the design of a 34x34 antenna array [12].…”

Section: Review Of Related Literaturementioning

confidence: 99%

Analysis of the Various Properties of an Antenna Array’s Radiation

2020

IJETER

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As technological innovations improve over time, antennas have become an inherent piece of our everyday lives and it is essential for individuals to understand how data is moved through these devices. There are different methods of deciding how energy can be transmitted by antennas in an efficient manner, and not all things are seen on the antennas themselves, as there are a few issues that may emerge from the transmission cables that they are associated with too. A common method of deciding how an antenna can transmit signals of energy is through the analysis of its radiation pattern. The radiation pattern of an antenna is able to determine how energy is radiated or data is propagated by a particular antenna. This analysis will focus on understanding the graphs of radiation patterns, beam scanning, patterns of arrays, and other types of graphs. Understanding all of these concepts are important in order to have the ability to effectively utilize antennas such as being able to maximize the amount of distance possible when correctly positioned and also having the ability to boost signals from other devices.

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“…In [13], SSA algorithm is explained in a detailed manner and compared with a collection of state-of-the-art algorithms including particle swarm optimization, fire fly algorithm, gravitational search algorithm, and bat algorithm. In the literature, SSA is employed to solve several engineering problems having different characteristics such as electric power dispatch problem [14], design of photovoltaic cell models [15], wireless sensor networks [16], variable speed wind generators [17], and conformal antenna array design [18] owing to its simplicity and high performance.…”

Section: Introductionmentioning

confidence: 99%

Sidelobe level suppression for elliptical antenna arrays using modified SALP swarm algorithm

Kurt

Başbuğ

Güney

2022

Journal of Electrical Engineering

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In this study, a modified version of salp swarm algorithm (MSSA) is used to synthesize elliptical antenna arrays (EAAs). The original salp swarm algorithm (SSA) is an optimization algorithm inspired by the behavior of salps in nature, which is used to solve engineering problems. The main purpose of the synthesis in this study is to obtain an EAA pattern with low maximum sidelobe levels (MSLs) for a fixed narrow first null beamwidth (FNBW). For different examples, the amplitude and angular position values of the antenna array elements are considered as optimization parameters. To show the effectiveness of the MSSA, eight examples of EAAs with 8, 12, and 20 elements are given. The results obtained with MSSA are compared with those of the antlion optimization, symbiotic organizations search, flower pollination algorithm, and accelerated particle swarm optimization from the literature. It is clear from the numerical results that MSSA outperforms the other algorithms in terms of the suppression of MSL.

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Side lobe pattern synthesis using hybrid SSWOA algorithm for conformal antenna array

Cited by 18 publications

References 26 publications

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

Analysis of the Various Properties of an Antenna Array’s Radiation

Sidelobe level suppression for elliptical antenna arrays using modified SALP swarm algorithm

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