• DocumentCode
    3642134
  • Title

    Efficient distributed resampling for particle filters

  • Author

    Balakumar Balasingam;Miodrag Bolić;Petar M. Djurić;Joaquín Míguez

  • Author_Institution
    School of Information Technology and Engineering, University of Ottawa (Canada)
  • fYear
    2011
  • fDate
    5/1/2011 12:00:00 AM
  • Firstpage
    3772
  • Lastpage
    3775
  • Abstract
    In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architectures with concurrent processing elements (PEs). The objective of distributed resampling is to reduce the communication among the PEs while not compromising the performance of the particle filter. An additional objective for implementation is to reduce the communication among the PEs. In this paper, we report an improved version of the distributed resampling algorithm that optimally selects the particles for communication between the PEs of the distributed scheme. Computer simulations are provided that demonstrate the improved performance of the proposed algorithm.
  • Keywords
    "Copper","Signal processing algorithms","Probability density function","Signal processing","Markov processes","Approximation algorithms","Covariance matrix"
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    2379-190X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5947172
  • Filename
    5947172