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Semi-independent resampling for particle filtering

  • Université Paris-Saclay
  • Université de Lille

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

Among sequential Monte Carlo methods, sampling importance resampling (SIR) algorithms are based on importance sampling and on some (resampling-based) rejuvenation algorithm that aims at fighting against weight degeneracy. However, this mechanism tends to be insufficient when applied to informative or high-dimensional models. In this letter, we revisit the rejuvenation mechanism and propose a class of parameterized SIR-based solutions that enable us to adjust the tradeoff between computational cost and statistical performances.

Original languageEnglish
Pages (from-to)130-134
Number of pages5
JournalIEEE Signal Processing Letters
Volume25
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Keywords

  • Particle filters
  • Resampling
  • Sequential Monte Carlo algorithms

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