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GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model Cover

GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model

By: Meriem Jgouta and  Benayad Nsiri  
Open Access
|Apr 2017

References

  1. 1. Azami, H., Malekzadeh, M. and Sanei, S. (2013) Optimization of orthogonal polyphase coding waveform for MIMO radar based on evolutionary algorithms, Journal of mathematics and Computer Science, Vol. 6, pp. 146-153.
  2. 2. Briers, M., Doucet, A. and Maskell, S. (2010) Smoothing algorithms for state-space models. Annals of the Institute of Statistical Mathematics, Springer, pp.61-89.10.1007/s10463-009-0236-2
  3. 3. Cui, X.H. and Polok, T.E. (2005) Document clustering using particle swarm optimization. In: Proceedings of swarm intelligence symposium, IEEE, pp. 185-191, Los Alamitos.10.1109/SIS.2005.1501621
  4. 4. Daehee Won, Precise Positioning, http://smileforday.com/?page_id=84
  5. 5. Dehuri, S. and Tripathy, S. (2011) An extended bayesian/HAPSO intelligent method in intrusion detection system. Knowledge Mining Using Intelligent Agents, Vol. 6, pp. 133.
  6. 6. GPSTk, The GPS Toolkit, http://www.gpstk.org.
  7. 7. IGS Data, http://sopac.ucsd.edu/dataBrowser.html.
  8. 8. Jgouta, M. and Nsiri, B. (2015) Statistical estimation of GNSS pseudo-range errors, Procedia Computer Science, Elsevier, vol. 73, pp. 258-265.
  9. 9. Jwo, D.J. and Weng, T.P. (2008) An adaptive sensor fusion method with applications in integrated navigation, Journal of Navigation, Vol. 61, No. 4, pp.705-721.
  10. 10. Leonard, J.A. and Kramer, M.A. (1991) Radial basis function networks for classifying process faults, Control Systems, IEEE, Vol. 11, No. 3, pp. 31-38.
  11. 11. Li, J. and Li, B. (2014) Parameters selection for support vector machine based on particle swarm optimization. In Intelligent Computing Theory, Springer International Publishing, pp. 41-47.10.1007/978-3-319-09333-8_5
  12. 12. Mosavi, MR. and Rahemi, N. (2015) Positioning performance analysis using RWLS algorithm based on variance estimation methods, Aerospace Science and Technology, pp.88-96.
  13. 13. Mussi, L., Cagnoni, S. and Daolio, F. (2009) GPU-based road sign detection using particle swarm optimization, International Conference on Intelligent Systems Design and applications, pp. 152-157.
  14. 14. NGA, National Geospatial-Intelligence Agency, http://eartch-info.nga.mil/GandG/Sathtml/.
  15. 15. Noureldin, A., Osman, A. and Elsheimy, N. (2004) A neuro-wavelet method for multi-sensor system integration for vehicular navigation, Measurement Science and Technology, Vol. 15, No. 2, pp. 404-412.
  16. 16. Santerre, R. Roy, E. and Parrot, D. (1995) Positionnement GPS avec des measures de pseudo distance filtrées et lissées, Lighthouse-Burlington, pp. 21-30.
  17. 17. Shen, C. Cao, G.Y and Zhu, X.J. (2002) Nonlinear modelling of MCFC stack based on RBF neural networks identification, Simulation Modelling Practice and Theory, Vol.10, No.1, pp.109-119.
  18. 18. Sun, T-Y., Liu, C-C., Lin, C-L., Hsieh, S-T. and Huang, C-S. (2009) A radial basis function neural network with adaptive structure via particle swarm optimization. - http://www.intechopen.com/books/particle_swarm_optimization/a_radial_basis_function_neural_network_with_adaptive_structure_via_particle_swarm_optimization.10.5772/6763
DOI: https://doi.org/10.1515/ttj-2017-0014 | Journal eISSN: 1407-6179 | Journal ISSN: 1407-6160
Language: English
Page range: 146 - 154
Published on: Apr 26, 2017
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2017 Meriem Jgouta, Benayad Nsiri, published by Transport and Telecommunication Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.