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An optimal circular antenna array design considering the mutual coupling employing ant lion optimization

Published online by Cambridge University Press:  09 July 2020

Avishek Das*
Affiliation:
Department of Electronics and Communication Engineering, HIT, Haldia, 721657, India
Durbadal Mandal
Affiliation:
Department of Electronics and Communication Engineering, NIT, Durgapur, 713209, India
Rajib Kar
Affiliation:
Department of Electronics and Communication Engineering, NIT, Durgapur, 713209, India
*
Author for correspondence: Avishek Das, E-mail: avishek.uit0408@gmail.com

Abstract

This paper presents an efficient approach for the design of a non-uniform single ring circular antenna array (CAA) for the synthesis of the optimal far-field radiation pattern. A recently proposed meta-heuristic-based optimization technique known as ant lion optimization (ALO) is applied in this paper to determine the optimum set of current amplitude excitation weights and the inter-element distance among the array elements to reduce the side lobe level (SLL) and 3-dB beam width considering the mutual coupling effect. The results achieved by employing the ALO algorithm are compared with the uniform radiation pattern and with those of the recently reported literature containing equal sets of elements to prove the superiority of ALO algorithm. Three different design examples of 8, 10, and 12 elements CAA are presented, and their performances are compared to illustrate the capability of the ALO algorithm-based approach over those of the recently reported literature.

Type
Antenna Design, Modelling and Measurements
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2020

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References

Balanis, CA (1997) Antenna Theory Analysis and Design, 2nd Edn. New York: John Willey and Son.Google Scholar
Elliott, RS (2003) Antenna Theory and Design, Revised Edn. New Jersey: IEEE Press.CrossRefGoogle Scholar
Lui, HS, Hui, HT and Leong, MS (2009) A note on the mutual-coupling problems in transmitting and receiving antenna arrays. IEEE Antennas and Propagation Magazine 51, 171176.Google Scholar
Gupta, I and Ksienski, A (1983) Effect of mutual coupling on the performance of adaptive arrays. IEEE Transactions on Antennas and Propagation 31, 785791.CrossRefGoogle Scholar
Chakravorty, P and Mandal, D (2016) Radiation pattern correction in mutually coupled antenna arrays using parametric assimilation technique. IEEE Transactions on Antennas and Propagation 64, 40924095.CrossRefGoogle Scholar
Das, A, Mandal, D, Ghoshal, SP and Kar, R (2017) An efficient Side lobe reduction technique considering mutual coupling effect in linear array antenna using BAT algorithm. Swarm and Evolutionary Computation 35, 2640.CrossRefGoogle Scholar
Mandal, D, Ghoshal, SP and Bhattacharjee, AK (2011) Wide null control of symmetric linear antenna array using novel particle swarm optimization. International Journal of RF and Microwave Computer-Aided Engineering 21, 376382.CrossRefGoogle Scholar
Haupt, RL and Werner, DH (2007) Genetic algorithms in electromagnetics. IEEE Press & Willey-Interscience.Google Scholar
Haupt, RL (1995) An Introduction to genetic algorithm for electromagnetics. IEEE Antennas and Propagation Magazine 37, 715.CrossRefGoogle Scholar
Panduro, MA, Mendez, AL, Dominguez, R and Romero, G (2006) Design of non-uniform circular antenna arrays for side lobe reduction using the method of genetic algorithm. International Journal of Electronics Communication (AEU) 60, 713717.CrossRefGoogle Scholar
Kennedy, J and Eberhart, R (1995) Particle swarm optimization, ICNN’95– International Conference on Neural Network, Perth, WA, Australia, vol. 4, pp. 19421948.Google Scholar
Boehringer, DW and Werner, DH (2004) Particle swarm optimization versus genetic algorithm for phased array synthesis. IEEE transaction on Antennas and Propagation 52, 771779.CrossRefGoogle Scholar
Sahib, M, Najjar, Y, Dib, N and Khodier, M (2008) Design of non-uniform circular antenna arrays using the particle swarm optimization. Journal of Electrical Engineering 59, 216220.Google Scholar
Ingber, L (1993) Simulated annealing: practice versus theory. Mathematical and Computer Modelling 18, 2957.CrossRefGoogle Scholar
Rattan, M, Patterh, MS and Sohi, BS (2009) Optimization of circular antenna arrays of isotropic radiators using simulated annealing. International Journal of Microwave and Wireless Technologies 1, 441446.CrossRefGoogle Scholar
Singh, U and Kamal, TS (2011) Design of non-uniform circular antenna arrays using biogeography-based optimization. IET Microwaves, Antennas and Propagation 5, 13651370.CrossRefGoogle Scholar
Sharaqa, A and Dib, N (2013) Circular antenna array synthesis using firefly algorithm. International Journal of RF and Microwave Computer-Aided Engineering 24, 139146.CrossRefGoogle Scholar
Morabito, AF, Donato, LD and Isernia, T (2018) Orbital angular momentum antennas: understanding actual possibilities through the aperture antennas theory. IEEE Antennas and Propagation Magazine 60, 5967.CrossRefGoogle Scholar
Mirjalili, S (2015) The ant lion optimizer. Advances in Engineering Software 83, 8098.CrossRefGoogle Scholar
Saxena, P and Kothari, A (2016) Ant lion optimization algorithm to control side lobe level and null depths in linear antenna arrays. International Journal of Electronics and Communication (AEU) 70, 13391349.CrossRefGoogle Scholar
Gupta, E and Saxena, A (2016) Performance evaluation of antlion optimizer based regulator in automatic generation control of interconnected power system. Journal of Engineering 2016, 4570617.CrossRefGoogle Scholar
Tung, NS and Chakravorty, S (2016) Ant lion optimizer based approach for optimal scheduling of thermal units for small scale electrical economic power dispatch problem. International Journal of Grid and Distributed Computing 9, 211224.CrossRefGoogle Scholar
Das, A, Mandal, D, Ghoshal, SP and Kar, R (2018) Moth flame optimization-based design of linear and circular antenna array for side lobe reduction. International Journal of Numerical Modelling-Electronic Networks. Devices and Fields 32, 115.Google Scholar
Eiben, AE and Smit, SK (2011) Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evolutionary Computation 1, 1931.CrossRefGoogle Scholar
De, BP, Kar, R, Mandal, D and Ghoshal, SP (2016) Soft computing-based approach for the optimal design of on-chip comparator and folded-cascode op-amp using colliding bodies optimization. International Journal of Numerical Modelling Electronic Networks. Devices and Fields 29, 873896.CrossRefGoogle Scholar