Advertisement

A Quantized Invasive Weed Optimization Based Antenna Array Synthesis with Digital Phase Control

  • Ratul Majumdar
  • Ankur Ghosh
  • Souvik Raha
  • Koushik Laha
  • Swagatam Das
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)

Abstract

The design of antenna arrays aims at minimizing side-lobe levels far as practicable. So a major concern of designer is to optimize the side lobes to increase directivity, gain, and efficiency. Invasive Weed Optimization (IWO) is a recently developed, ecologically inspired metaheuristic algorithm that has already found some major applications in electromagnetic research. In this article the synthesis of array antenna pattern by digital phase shifters is accomplished with a modified version of the IWO algorithm called QIWO (Quantized Invasive Weed Optimization. The proposed algorithm searches for optimal solution of the fitness function, which contains the SLL value and the interference suppression keeping the main beam unchanged. The results obtained from this algorithm are better than that of QPSO (Quantized Particle Swarm Optimization) and BPSO (Binary Particle Swarm Optimization). In this paper the array factor is expressed mathematically by a linear transform, which is similar to Discrete Cosine Transform (DCT). This proposed algorithm is also found to be efficient in computing for large arrays.

Keywords

Particle Swarm Optimization Discrete Cosine Transform Metaheuristic Algorithm Main Beam Interference Suppression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baird, D., Rassweiler, G.: Adaptive sidelobe nulling using digitally controlled phase shifters. IEEE Trans. Antennas Propag. 24(5), 638–649 (1976)CrossRefGoogle Scholar
  2. 2.
    Steyskal, H., Shore, R.A., Haupt, R.L.: Methods for null control and their effects on radiation pattern. IEEE Trans. Antennas Propag. 34, 404–409 (1986)CrossRefGoogle Scholar
  3. 3.
    Haupt, R.L.: Phase-only adaptive nulling with a genetic algorithm. IEEE Trans. Antennas Propag. 45(6), 1009–1015 (1997)CrossRefGoogle Scholar
  4. 4.
    Mehrabian, A.R., Lucas, C.: A novel numerical optimization algorithm inspired from weed colonization. Ecological Informatics 1, 355–366 (2006)CrossRefGoogle Scholar
  5. 5.
    Oliveri, G., Poli, L.: Synthesis of monopulse sub-arrayed linear and planar array antennas with optimized sidelobes. Progress In Electromagnetics Research, PIER 99, 109–129 (2009)CrossRefGoogle Scholar
  6. 6.
    Ismail, T.H., Hamici, Z.M.: Array pattern sunthesis using digital phase control by quantized particle swarm optimization. IEEE Transactions on Antennas and Propagation 58(6), 2142–2145 (2010)CrossRefGoogle Scholar
  7. 7.
    Jin, N., Rahmat-Samii, Y.: Advances in particle swarm optimization for antenna designs: Real-number, binary, single-objective and multiobjective implementations. IEEE Trans. Antennas Propag. 55(3), 556–567 (2007)CrossRefGoogle Scholar
  8. 8.
    Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: IEEE Int. Conf. Man Syst., vol. 5, pp. 4104–4108 (October 1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ratul Majumdar
    • 1
  • Ankur Ghosh
    • 1
  • Souvik Raha
    • 1
  • Koushik Laha
    • 1
  • Swagatam Das
    • 1
  1. 1.Dept. of Electronics & Telecommunication Engg.Jadavpur UniversityKolkataIndia

Personalised recommendations