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Computational Intelligence in Data Mining - Volume 3 pp 499–507Cite as

Maximum Likelihood DOA Estimation in Wireless Sensor Networks Using Comprehensive Learning Particle Swarm Optimization Algorithm

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 33))

Abstract

Direction of arrival (DOA) estimation is one of the challenging problem in wireless sensor networks. Several methods based on maximum likelihood (ML) criteria have been established in literature. Generally, to obtain the ML solutions, the DOAs must be estimated by optimizing a complicated nonlinear multimodal function over a high-dimensional problem space. Comprehensive learning particle swarm optimization (CLPSO) based solution is proposed here to compute the ML functions and explore the potential of superior performances over traditional PSO algorithm. Simulation results confirms that the CLPSO-ML estimator is significantly giving better performance compared to conventional method like MUSIC in various scenarios at less computational costs.

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References

  1. Ziskind, I., Wax, M.: Maximum likelihood localization of multiple sources by alternating projection. IEEE Trans. Acoust. Speech Signal Process. 36, 1553–1560 (1988)

    Google Scholar 

  2. Schmidt, R.: Multiple emitter location and signal parameter estimation. IEEE Trans. Antennas Propag. 34, 276–280 (1986)

    Article  Google Scholar 

  3. Capon, J.: High-resolution frequency–wavenumber spectrum analysis. Proc. IEEE 57, 1408–1418 (1969)

    Article  Google Scholar 

  4. Krim, H., Viberg, M.: Two decades of array signal processing research: the parametric approach. IEEE Signal Process. Mag. 13, 67–94 (1996)

    Article  Google Scholar 

  5. Noel, M.M., Joshi, P.P., Jannett, T.C.: Improved maximum likelihood estimation of target position in wireless sensor networks using particle swarm optimization. In: Third International Conference on Information Technology: New Generations vol. 0, pp. 274–279 (2006)

    Google Scholar 

  6. Li, M., Lu, Y.: Maximum likelihood DOA estimation in unknown colored noise fields. IEEE Trans. Aerosp. Electron. Syst. 44, 1079–1090 (2008)

    Article  Google Scholar 

  7. Chung, P.J., Böhme, J.F.: Doa estimation using fast EM and SAGE algorithms. Signal Process 82, 1753–1762 (2002)

    Article  MATH  Google Scholar 

  8. Rodriguez, J., Ares, F., Moreno, E., Franceschetti, G.: Genetic algorithm procedure for linear array failure correction. Electron. Lett. 36, 196–198 (2000)

    Article  Google Scholar 

  9. Li, M., Lu, Y.: A refined genetic algorithm for accurate and reliable DOA estimation with a sensor array. Wirel. Pers. Commun. 43, 533–554 (2007)

    Article  Google Scholar 

  10. Panigrahi, T., Rao, D.H., Panda, G., Mulgrew, B., Majhi, B.: Maximum likelihood DOA estimation in distributed wireless sensor network using adaptive particle swarm optimization. In: ACM International Conference on Communication, Computing and Security (ICCCS2011) pp. 134–136 (2011)

    Google Scholar 

  11. Panigrahi, T., Panda, G., Majhi, B.: Maximum likelihood source localization in wireless sensor network using particle swarm optimization. Int. J. Signal Imaging Syst. Eng. 6, 83–90 (2013)

    Article  Google Scholar 

  12. Panigrahi, T., Panda, G., Mulgrew, B., Majhi, B.: Distributed doa estimation using clustering of sensor nodes and diffusion PSO algorithm. Swarm Evol. Comput. 9, 47–57 (2013)

    Google Scholar 

  13. Panigrahi, T., Panda, G., Mulgrew, B.: Distributed bearing estimation techniques using diffusion particle swarm optimization algorithm. IET Wireless Sens. Syst. 2, 385–393 (2012)

    Article  Google Scholar 

  14. Liang, J., Qin, A., Suganthan, P., Baskar, S.: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans. Evol. Comput. 10, 281–295 (2006)

    Article  Google Scholar 

  15. Trees, H.V.: Optimum array processing. 1em plus 0.5em minus 0.4em. Wiley-Interscience Publication, New York (2002)

    Google Scholar 

  16. Jaffer, A.G.: Maximum likelihood direction finding of stochastic sources: a separable solution. In: Proceedings of ICASSP, vol. 5, pp. 2893–2896 (1988)

    Google Scholar 

  17. Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE Conference Neural Network, vol. IV, pp. 1942–1948 (1948)

    Google Scholar 

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Authors and Affiliations

  1. Department of ECE, National Institute of Science and Technology, Berhampur, 761008, India

    Srinivash Roula, Harikrishna Gantayat & T. Panigrahi

  2. School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Odisha, India

    G. Panda

Authors
  1. Srinivash Roula
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  2. Harikrishna Gantayat
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  3. T. Panigrahi
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  4. G. Panda
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Corresponding author

Correspondence to Srinivash Roula .

Editor information

Editors and Affiliations

  1. School of Electrical and Information Engineering, University of South Australia, South Australia, Australia

    Lakhmi C. Jain

  2. Computer Science and Engineering, Veer Surendra Sai University of Technolo, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Eng., National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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© 2015 Springer India

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Roula, S., Gantayat, H., Panigrahi, T., Panda, G. (2015). Maximum Likelihood DOA Estimation in Wireless Sensor Networks Using Comprehensive Learning Particle Swarm Optimization Algorithm. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_45

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  • DOI: https://doi.org/10.1007/978-81-322-2202-6_45

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2201-9

  • Online ISBN: 978-81-322-2202-6

  • eBook Packages: EngineeringEngineering (R0)

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