Skip to content


  • Research Article
  • Open Access

Resampling Algorithms for Particle Filters: A Computational Complexity Perspective

EURASIP Journal on Advances in Signal Processing20042004:403686

  • Received: 30 April 2003
  • Published:


Newly developed resampling algorithms for particle filters suitable for real-time implementation are described and their analysis is presented. The new algorithms reduce the complexity of both hardware and DSP realization through addressing common issues such as decreasing the number of operations and memory access. Moreover, the algorithms allow for use of higher sampling frequencies by overlapping in time the resampling step with the other particle filtering steps. Since resampling is not dependent on any particular application, the analysis is appropriate for all types of particle filters that use resampling. The performance of the algorithms is evaluated on particle filters applied to bearings-only tracking and joint detection and estimation in wireless communications. We have demonstrated that the proposed algorithms reduce the complexity without performance degradation.

Keywords and phrases

  • particle filters
  • resampling
  • computational complexity
  • sequential implementation

Authors’ Affiliations

Department of Electrical and Computer Engineering, State University of New York at Stony Brook, Stony Brook, NY 11794-2350, USA


© Bolić et al. 2004