Resampling Methods for Particle Filtering: Classification, implementation, and strategies

Two decades ago, with the publication, we witnessed the rebirth of particle filtering (PF) as a methodology for sequential signal processing. Since then, PF has become very popular because of its ability to process observations represented by nonlinear state-space models where the noises of the model can be non-Gaussian. This methodology has been adopted in various fields, including finance, geophysical systems, wireless communications, control, navigation and tracking, and robotics. The popularity of PF has also spurred the publication of several review articles. In this article, the state of the art of resampling methods was reviewed. The methods were classified and their properties were compared in the…

• NS
  National Science Foundation
• NU
  Northwestern University
• NN
  National Natural Science Foundation of China
• NP
  Northwestern Polytechnical University
• SB
  Stony Brook University