On Resampling Algorithms for Particle Filters

TLDR

The study compares four common resampling algorithms for particle filters and introduces a theoretical framework to analyze their differences. The authors develop this framework and validate it with extensive Monte Carlo simulations to assess resampling quality and computational complexity. The results show that systematic resampling outperforms the others in both quality and computational efficiency.

Abstract

In this paper a comparison is made between four frequently encountered resampling algorithms for particle filters. A theoretical framework is introduced to be able to understand and explain the differences between the resampling algorithms. This facilitates a comparison of the algorithms with respect to their resampling quality and computational complexity. Using extensive Monte Carlo simulations the theoretical results are verified. It is found that systematic resampling is favourable, both in terms of resampling quality and computational complexity.