Simplified partial resampling method for state estimation usingparticle filter

  • Authors

    • M Tirumala Reddy
    • Y Sri Ganesh
    • Ch Lakshmi Gayathri
    • T Megha Shyam
    • S Koteswar Rao
    • V Gopi Tilak
    2018-03-18
    https://doi.org/10.14419/ijet.v7i2.7.10588
  • Particle Filters, Partial Resampling, Simple Pendulum, State Estimation.

  • Abstract

    Particle filter methods are used in the estimation and tracking of the objects for non-linear and non-gaussian noise conditions. In this paper work the object estimation using partial resampling methods are discussed. On using partial resampling method resampling becomes faster. The performance of particle filter with partial resampling scheme is analyzed using the state estima-tion of a simple pendulum.

  • References

    1. [1] Dan Simon, “Optimal State Estimation Kalman, H∞, and Nonlinear Approaches", John Wiley and sonsinc, publishers.

      [2] Simo Sarkka, “Bayesian Filtering and Smoothingâ€, Cambridge University Press.

      [3] Simo Sarkka, “Bayesian Estimation of Time-Varying Systemsâ€, Copyright (C) Simo Sarakka, 2009–2012.

      [4] G.Kitagawa, “Monte Car10 filter and smoother for nonGaussiannonlinear state space models,†Journal ofComputational and Graphical Statistics, 5(l) pp. 1-25 (1996)

      [5] Doucet, A., De Freitas, N., and Gordon, N. 2001. Sequential Monte Carlo Methods in Practice. Springer.

      [6] Sangjin Hong. "New resampling algorithms for particle filters", 2003 IEEE International Conference on Acoustics Speech and Signal Processing 2003 Proceedings (ICASSP 03) ICASSP-03, 2003.

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  • How to Cite

    Tirumala Reddy, M., Sri Ganesh, Y., Lakshmi Gayathri, C., Megha Shyam, T., Koteswar Rao, S., & Gopi Tilak, V. (2018). Simplified partial resampling method for state estimation usingparticle filter. International Journal of Engineering & Technology, 7(2.7), 243-245. https://doi.org/10.14419/ijet.v7i2.7.10588

    Received date: 2018-03-25

    Accepted date: 2018-03-25

    Published date: 2018-03-18