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New resampling algorithms for particle filters

  • Stony Brook University

Research output: Contribution to journalConference articlepeer-review

99 Scopus citations

Abstract

Resampling is a critically important operation in the implementation of particle filtering. In parallel hardware implementations, resampling becomes a bottleneck due to its sequential nature and the increased complexity it imposes on the traffic of the designed interconnection network. To circumvent some of these difficulties, we propose two new resampling algorithms. The first one, called residual-systematic resampling, combines the merits of both systematic and residual resampling and is suitable for pipelined implementation. It also guarantees fixed duration of the resampling procedure irrespective of the weight distribution of the particles. The second algorithm, referred to as partial resampling, has low complexity and reduces traffic load through the hardware network. These two algorithms should also be considered as resampling methods in simulations on standard computers.

Original languageEnglish
Pages (from-to)589-592
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
StatePublished - 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: Apr 6 2003Apr 10 2003

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