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Optimization of Linear Arrays using Modified Social Group Optimization Algorithm

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Title Optimization of Linear Arrays using Modified Social Group Optimization Algorithm
 
Creator Srikala, E V S D N S L K
Murali, M
Krishna, M Vamshi
Raju, G S N
 
Subject Linear arrays
MSGOA
Optimization
Patterns
Sidelobe levels
 
Description 354-359
In this paper, optimization of the linear array (LA) antenna is performed using modified social group optimization algorithm (SGOA). First step of the work involves in transforming the electromagnetic engineering problem to an optimization problem which is completely described in terms of objectives. Linear array synthesis is inherently considered as a multi-attribute problem. The pattern synthesis of LA is carried out with several objectives involving sidelobe level (SLL), beam-width (BW) and desired nulls. The SLL suppression with BW constraint is considered as first objective of this work and the results are compared with several evolutionary computing algorithms like ant lion (ALO), grey wolf (GWO) and root-runner (RRA). Following this, the MSGOA is further used to synthesise null patterns in which the pattern is completely described in terms of nulls with SLL and BW as constraints. The entire simulation-based experimentation is performed using Matlab® on i5 computing system.
 
Date 2021-06-14T06:58:53Z
2021-06-14T06:58:53Z
2021-04
 
Type Article
 
Identifier 0975-1084 (Online); 0022-4456 (Print)
http://nopr.niscair.res.in/handle/123456789/57474
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source JSIR Vol.80(04) [April 2021]