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Synthesis of hexagonal planar array using swarm-based optimization algorithms

Published online by Cambridge University Press:  12 May 2014

Anirban Chatterjee  and
Debasis Mandal
Anirban Chatterjee*
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Goa, Farmagudi, Ponda, Goa, India
Debasis Mandal
Affiliation:
Department of Electronics and Communication Engineering, Bengal College of Engineering and Technology, Durgapur, India
*
Corresponding author: A. Chatterjee Email: [email protected]
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Abstract

Nature inspired optimization algorithms, namely artificial bee colony (ABC) optimization and firefly algorithm (FA), have been applied to synthesize beam patterns of a hexagonal planar array of isotropic elements. Two different cases, comprising two different beam patterns of a pencil beam and a square footprint pattern over a bounded region with lower peak sidelobe levels are presented. The pencil beam is generated by thinning the uniformly excited array and the square footprint pattern is generated by imposing optimum amplitudes, phases, and their corresponding states (“on”/“off”) to the array elements. The optimum values of the parameters for both the cases are computed using ABC and FA individually, and the superiority of FA over ABC for the proposed problem in terms of computing solutions for both the cases is established.

Keywords

Optimization algorithmArtificial bee colony (ABC) algorithmFirefly algorithm (FA)Hexagonal planar arraySidelobe level (SLL)Square footprintThinning
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 7 , Issue 2 , April 2015 , pp. 151 - 160
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2014 

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References

REFERENCES

[1]Van Trees, H.L.: Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory, John Wiley & Sons, Inc., New York, USA, 2002.Google Scholar
[2]Goto, N.: A synthesis of array antennas for high directivity and low sidelobes. IEEE Trans. Antennas Propag., 20 (4) (1972), 427–432.Google Scholar
[3]Goto, N.: Pattern synthesis of hexagonal planar arrays. IEEE Trans. Antennas Propag., 20 (4) (1972), 479–481.Google Scholar
[4]Gozasht, F.; Dadashzadeh, G.R.; Nikmhr, S.: A comprehensive performance study of circular and hexagonal array geometries in the LMS algorithm for smart antenna applications. Prog. Electromagn. Res., 68 (2007), 281–296.Google Scholar
[5]Mahmoud, K.R.; El-Adawy, M.; Ibrahem, S.M.M.; Bansal, R.; Zainud-Deen, S.H.: A comparison between circular and hexagonal array geometries for smart antenna systems using particle swarm optimization algorithm. Prog. Electromagn. Res., 72 (2007), 75–90.Google Scholar
[6]Bucci, O.M.; Isernia, T.; Morabito, A.F.: A deterministic approach to the synthesis of pencil beams through planar thinned arrays. Prog. Electromagn. Res., 101 (2010), 217–230.Google Scholar
[7]Johnson, J.M.; Rahmat-Samii, Y.: Genetic algorithms and method of moments (GA/MOM) for the design of integrated antennas. IEEE Trans. Antennas Propag., 47 (10) (1999), 1606–1614.Google Scholar
[8]Herscovici, N.; Osorio, M.F.; Peixeiro, C.: Miniaturization of rectangular microstrip patches using genetic algorithms. IEEE Antennas Wirel. Propag. Lett., 1 (1) (2002), 94–97.Google Scholar
[9]Soontornpipit, P.; Furse, C.M.; Chung, Y.C.: Miniaturized biocompatible microstrip antenna using genetic algorithms. IEEE Trans. Antennas Propag., 53 (6) (2005), 1939–1945.Google Scholar
[10]Jayasinghe, J.W.; Anguera, J.; Uduwawala, D.N.: A simple design of multi band microstrip patch antennas robust to fabrication tolerances for GSM, UMTS, LTE, and bluetooth applications by using genetic algorithm optimization. Prog. Electromagn. Res. M, 27 (2012), 255–269.Google Scholar
[11]Jayasinghe, J.M.J.W.; Anguera, J.; Uduwawala, D.N.: Genetic algorithm optimization of a high-directivity microstrip patch antenna having a rectangular profile. Radioengineering, 22 (3) (2013), 700–707.Google Scholar
[12]Mailloux, R.J.: Phased Array Antenna Handbook, 2nd ed., Artech House, Boston, 2005.Google Scholar
[13]Quevedo-Teruel, Ó.; Rajo-Iglesias, E.: Ant colony optimization in thinned array synthesis with minimum sidelobe level. IEEE Antennas Wirel. Propag. Lett., 5 (1) (2006), 349–352.Google Scholar
[14]Haupt, R.L.: Thinned concentric ring array, in Proc. IEEE Antennas and Propagation Int. Symp., 2008, 1–4.Google Scholar
[15]Pathak, N.; Mahanti, G.K.; Singh, S.K.; Mishra, J.K.; Chakraborty, A.: Synthesis of thinned planar circular array antennas using modified particle swarm optimization. Prog. Electromagn. Res. Lett., 12 (2009), 87–97.Google Scholar
[16]Chatterjee, A.; Mahanti, G.K.; Pathak, N.N.: Comparative performance of gravitational search algorithm and modified particle swarm optimization algorithm for synthesis of thinned scanned concentric ring array antenna. Prog. Electromagn. Res. B, 25 (2010), 331–348.Google Scholar
[17]Zhang, L.; Jiao, Y.-C.; Weng, Z.-B.; Zhang, F.-S.: Design of planar thinned arrays using a Boolean differential evolution algorithm. IET Microw. Antennas Propag., 4 (2010), 2172–2178.Google Scholar
[18]Petko, J.S.; Werner, D.H.: “Pareto optimization of thinned planar arrays with elliptical mainbeams and low sidelobe levels. IEEE Trans. Antennas Propag., 59 (4) (2011), 1748–1751.Google Scholar
[19]Elliott, R.S.; Stern, G.J.: Footprint patterns obtained by planar arrays. Inst. Elect. Eng. Proc., 137 (1990), 108–112.Google Scholar
[20]Ares, F.; Elliott, R.S.; Moreno, E.: Design of planar arrays to obtain efficient footprint patterns with an arbitrary footprint boundary. IEEE Trans. Antennas Propag., 42 (11) (1994), 1509–1514.Google Scholar
[21]Ares-Pena, F.J., Franceschetti, G.; Rodriguez, J.A.: A simple alternative for beam reconfiguration of array antennas. Prog. Electromagn. Res., 88 (2008), 227–240.Google Scholar
[22]Eirey-Perez, R.; Álvarez-Folqueiras, M.; Rodriquez-González, J.A.; Ares-Pena, F.: Arbitrary footprints from arrays with concentric ring geometry and low dynamic range ratio. J. Electromagn. Waves Appl., 24 (13) (2010), 1795–1806.Google Scholar
[23]Karaboga, D.; Basturk, B.: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems, In LNCS: Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing, Springer-Verlag, 2007, vol. 4529, 789–798.Google Scholar
[24]Karaboga, D.; Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Global Optim., 39 (3) (2007), 459–471.Google Scholar
[25]Yang, X.S.: Firefly algorithms for multimodal optimization, in Stochastic Algorithms: Foundations and Applications, Lecture Notes in Computer Sciences, vol. 5792, Springer, Berlin, 2009, 169–178.Google Scholar
[26]Łukasik, S.; Żak, S.: Firefly algorithm for continuous constrained optimization tasks, in Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems, Lecture Notes in Computer Science, vol. 5796, Springer, Berlin, 2009, 97–106.Google Scholar
[27]Yang, X.S.: Engineering Optimization: An Introduction with Metaheuristic Applications, John Wiley & Sons, New Jersey, 2010.Google Scholar