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Directivity improvement and optimal far field pattern of time modulated concentric circular antenna array using hybrid evolutionary algorithms

Published online by Cambridge University Press:  25 June 2015

Gopi Ram*
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Durgapur, India
Durbadal Mandal
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Durgapur, India
Rajib Kar
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Durgapur, India
Sakti Prasad Ghoshal
Affiliation:
Department of Electrical Engineering, National Institute of Technology Durgapur, India
*
Corresponding author: G. Ram Email: gopi203hardel@gmail.com

Abstract

In this paper time modulated nine-ring concentric circular antenna array (TMCCAA) using fitness based novel hybrid adaptive differential evolution with particle swarm optimization (ADEPSO) has been studied. ADEPSO is hybrid of fitness based adaptive differential evolution and particle swarm optimization (PSO). Differential evolution is a simple and robust evolutionary algorithm but sometimes causes instability problem; PSO is also a simple, population based robust evolutionary algorithm but has the problem of sub-optimality. ADEPSO has overcome the above individual disadvantages faced by both the algorithms and is used for the design of TMCCAA. The comparative case studies as Case-1 and Case-2 are made with three control parameters like uniform inter-element spacing in rings, inter-ring radii and the switching “ON” times of rings. The same array radiates at various harmonic frequencies. The first two harmonic frequencies have been considered in this work. The numerical results show Case-2, outperforms Case-1 with respect to better side lobe level (SLL), and more improved directivity. Apart from this, the authors have computed powers radiated at the center/fundamental frequency and the first two sideband frequencies, and dynamic efficiency. It is found that power radiated by any sideband frequency is very less as compared with the power radiated at the center frequency. It has been observed that as the sideband frequency increases, side band level decreases to the greater extent as compared with SLL. The aperture size is a very important constraint for the array, since there is an upper limit for the aperture size of a given array in real-life environment. Hence, in our optimization design, the maximum radius of the concentric ring array is constrained.

Type
Research Papers
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2015 

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References

REFERENCES

[1] Ballanis, A.: Antenna Theory Analysis and Design, 2nd ed., John Willey and Son's Inc., New York, 1997.Google Scholar
[2] Elliott, R.S.: Antenna Theory and Design, Revised ed., John Wiley, New Jersey, 2003.Google Scholar
[3] Shanks, H.E.; Bickmore, R.W.: Four-dimensional electromagnetic radiators. Canad. J. Phys., 37 (1959), 263275.Google Scholar
[4] Kummer, W.H., Villeneuve, A.T., Fong, T.S., Terrio, F.: Ultra-low sidelobes from time-modulated arrays. IEEE Trans. Antennas Propag., 11 (5) (1963), 633639.Google Scholar
[5] Lewis, B.L., Evins, J.B.: A new technique for reducing radar response to signals entering antenna sidelobes. IEEE Trans. Antennas Propag., 31 (6) (1983), 993996.Google Scholar
[6] Yang, S., Gan, Y.B.; Qing, A.: ‘Sideband suppression in time modulated linear arrays by the differential evolution algorithm. IEEE Antennas Wireless Propag. Lett., 1 (2002), 173175.Google Scholar
[7] Yang, S., Gan, Y.B.; Tan, P.K.: ‘A new technique for power-pattern synthesis in time-modulated linear arrays. IEEE Antennas Wireless Propag. Lett., 2 (2003), 285287.Google Scholar
[8] Fondevila, J., Bregains, J.C., Ares, F.; Moreno, E.: Optimizing uniformly excited arrays through time modulation. IEEE Antennas Wireless Propag. Lett., 3 (2004), 298301.Google Scholar
[9] Yang, S., Gan, Y.B., Qing, A.; Tan, P.K.: Design of a uniform amplitude time modulated linear array with optimized time sequences. IEEE Trans. Antennas Propag., 53 (7) (2005), 23372339.Google Scholar
[10] Yang, S., Gan, Y.B.; Qing, A.: Antenna array pattern nulling using a differential evolution algorithm. Int. J. RF Microw. Comput.-Aided Eng., 14 (2004), 5763.Google Scholar
[11] Zhu, Q.; Yang, S.; Zheng, L.; Nie, Z.: Design of a low sidelobe time modulated linear array with uniform amplitude and sub-sectional optimized time steps. IEEE Trans. Antennas Propag., 60 (9) (2012), 44364439.Google Scholar
[12] Yang, S.; Gan, Y.B.; Tan, P.K.: Evaluation of directivity and gain for time-modulated linear antenna arrays. Microw. Opt. Technol. Lett., 42 (2) (2004), 167171.Google Scholar
[13] Das, R.: Concentric ring array. IEEE Trans. Antennas Propag., 14 (3) (1966), 398400.Google Scholar
[14] Stearns, C.; Stewart, A.: An investigation of concentric ring antennas with low sidelobes. IEEE Trans. Antennas Propag., 13 (6) (1965), 856863.Google Scholar
[15] Goto, N.; Cheng, D.K.: On the synthesis of concentric-ring arrays. IEEE Proc., 58 (5) (1970), 839840.Google Scholar
[16] Huebner, M.D.A.: Design and optimization of small concentric ring arrays, in ProG. IEEE AP-S Symp., 1978, 455–445.Google Scholar
[17] Holtrup, M.G.; Margulnaud, A.; Citerns, J.: Synthesis of electronically steerable antenna arrays with element on concentric rings with reduced sidelobes, in Proc. IEEE AP-S Symp., 2001, 800803.Google Scholar
[18] Dessouky, M., Sharshar, H.; Albagory, Y.: Efficient sidelobe reduction technique for small-sized concentric circular arrays. Prog. Electromagn. Res., PIER 65 (2006), 187200.Google Scholar
[19] Haupt, R.L.: Optimized element spacing for low sidelobe concentric ring arrays. IEEE Trans. Antennas Propag., 56 (1) (2008), 266268.Google Scholar
[20] Munson, D.C.; O'Brian, J.D.; Jenkins, W.K.: A tomographic formulation of spot-light mode synthetic aperture radar. Proc. IEEE, 71 (1983), 917925.Google Scholar
[21] Compton, R.T.: An adaptive array in a spread-spectrum communication system. Proc. IEEE, 66 (1978), 289298.Google Scholar
[22] Haykin, S., Justice, J.H., Owsley, N.L., Yen, J.L., Kak, A.C.: Array Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1985.Google Scholar
[23] Panduro, M.A.; Mendez, A.L.; Dominguez, R.; Romero, G.: Design of non-uniform circular antenna arrays for side lobe reduction using the method of genetic algorithms. Int. J. Electron. Commun. (AEO), 60 (2006), 713717.Google Scholar
[24] Panduro, M.A., Brizuela, C.A.; Balderas, L.I.; Acosta, D.A.: A comparison of genetic algorithms, particle swarm optimization and the differential evolution method for the design of scannable circular antenna arrays. Prog. Electromagn. Res. B, 13 (2009), 171186.Google Scholar
[25] Kennedy, J.; Eberhart, R.C.: Particle swarm optimization, in IEEE Int. Conf. on Neural Networks, Piscataway, NJ, 1995, vol. 4, 19421948.Google Scholar
[26] Shihab, M., Najjar, Y., Dib, N.; Khodier, M.: Design of non-uniform circular antenna arrays using particle swarm optimization. J. Electr. Eng., 59 (4) (2008), 216220.Google Scholar
[27] Mandal, D., Ghoshal, S.P.; Bhattacharjee, A.K.: Design of concentric circular antenna array with central element feeding using particle swarm optimization with constriction factor and inertia weight approach and evolutionary programing technique. J. Infrared Millim. Terahertz Waves, 31 (6) (2010), 667680.Google Scholar
[28] Mandal, D., Ghoshal, S.P.; Bhattacharjee, A.K.: Radiation pattern optimization for concentric circular antenna array with central element feeding using craziness based particle swarm optimization. Int. J. RF Microw. Comput.-Aided Eng., 20 (5) (2010), 577586.Google Scholar
[29] Zheng, L., Yang, S., Zhu, Q.; Nie, Z.: Synthesis of pencil-beam patterns with time-modulated concentric circular ring antenna arrays, in PIERS Proc., Suzhou, China, September 2011, 372376.Google Scholar
[30] Storn, R.; Price, K.: Differential Evolution- a Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces, Technical Report, Int. Computer Science Institute, Berkley, 1995.Google Scholar
[31] Reddy, K.S.; Bharath, M.S.; Sahoo, S.K., Sinha, S., Reddy, J.P.: Design of low power, high performance FIR filter using modified differential evolution algorithm, in Int. Symp. on Electronic System Design, (ISED), 2011, 6266.Google Scholar
[32] Chattopadhyay, S., Sanyal, S.K.; Chandra, A.: A novel self-adaptive differential evolution algorithm for efficient design of multiplier-less low pass FIR filter, in Int. Conf. on Sustainable Energy and Intelligent Systems (SEISCON), 2011, 733738.Google Scholar
[33] Zhang, W., Xie, X.: DEPSO: Hybrid particle swarm with differential evolution operator. IEEE Int. Conf. Syst., Man and Cybernetics, 4 (2003), 38163821.Google Scholar
[34] Hao, Z.F.; Guo, G.H.; Huang, H.: A particle swarm optimization algorithm with differential evolution. Int. Conf. Machine Learning and Cybernetics, 2 (2007), 10311035.Google Scholar
[35] Ghoshal, A., Giri, R., Chowdhury, A., Das, S.; Abraham, A.: Two-channel quadrature mirror bank filter design using a fitness-adaptive differential evolution algorithm, in 2010 Second World Congress on Nature and Biologically Inspired Computing, 2010, 634641.Google Scholar
[36] Vasundhara, D.M.; Kar, R.; Ghoshal, S.P.: Digital FIR filter design using fitness based hybrid adaptive differential evolution with particle swarm optimization. Nat. Comput., 13 (1) (2014), 5564.Google Scholar
[37] Walpole, R.E.; Myer, R.H.: Probability and Statistics for Engineers and Scientists, Macmillan, New York, 1978.Google Scholar