The Optimum Design of Scanned Linear Antenna Array Using Sine Cosine Optimization Algorithm

In this article, the side lobe level (SLL) of the radiation pattern is reduced, and the first null beam width (FNBW) is kept constant by synthesizing symmetric scanning Linear Antenna Arrays (LAA), which is done by considering excitation amplitude as the optimization parameter. A Sine cosine algorit...

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Vydáno v:Wasit Journal of Computer and Mathematics Science Ročník 2; číslo 2; s. 87 - 96
Hlavní autoři: Al hussein M. Alturfi, Goyal, Sonia, Kaur, Amrit
Médium: Journal Article
Jazyk:angličtina
Vydáno: College of Computer and Information Technology – University of Wasit, Iraq 30.06.2023
ISSN:2788-5887, 2788-5879, 2788-5879, 2788-5887
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Abstract In this article, the side lobe level (SLL) of the radiation pattern is reduced, and the first null beam width (FNBW) is kept constant by synthesizing symmetric scanning Linear Antenna Arrays (LAA), which is done by considering excitation amplitude as the optimization parameter. A Sine cosine algorithm (SCA) is used to achieve this objective. Three different case studies are illustratedin this article to show the effectiveness of SCA in LAA optimization. The results obtained show that the SCA algorithm performs better than Firefly Algorithm (FA), Symbiotic Organisms Search (SOS), and hybrid optimization algorithm based on Grasshopper Optimization Algorithm (GOA) and Antlion Optimization (ALO)
AbstractList In this article, the side lobe level (SLL) of the radiation pattern is reduced, and the first null beam width (FNBW) is kept constant by synthesizing symmetric scanning Linear Antenna Arrays (LAA), which is done by considering excitation amplitude as the optimization parameter. A Sine cosine algorithm (SCA) is used to achieve this objective. Three different case studies are illustrated in this article to show the effectiveness of SCA in LAA optimization. The results obtained show that the SCA algorithm performs better than Firefly Algorithm (FA), Symbiotic Organisms Search (SOS), and hybrid optimization algorithm based on Grasshopper Optimization Algorithm (GOA) and Antlion Optimization (ALO)
In this article, the side lobe level (SLL) of the radiation pattern is reduced, and the first null beam width (FNBW) is kept constant by synthesizing symmetric scanning Linear Antenna Arrays (LAA), which is done by considering excitation amplitude as the optimization parameter. A Sine cosine algorithm (SCA) is used to achieve this objective. Three different case studies are illustratedin this article to show the effectiveness of SCA in LAA optimization. The results obtained show that the SCA algorithm performs better than Firefly Algorithm (FA), Symbiotic Organisms Search (SOS), and hybrid optimization algorithm based on Grasshopper Optimization Algorithm (GOA) and Antlion Optimization (ALO)
Author Al hussein M. Alturfi
Goyal, Sonia
Kaur, Amrit
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10.2528/PIERB11053108
10.1080/00207217.2019.1661028
10.1109/TAP.2011.2173111
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10.1109/ICCSP.2011.5739343
10.3923/jmcomm.2011.6.10
10.1109/MMS.2011.6068547
10.1016/j.knosys.2015.12.022
10.11591/ijece.v10i2.pp1477-1484
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10.2528/PIERB16032504
10.1016/j.asoc.2006.10.011
10.1109/MAPE.2011.6156156
10.1109/ICECENG.2011.6057613
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