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On Resampling Algorithms for Particle Filters
- Source :
- 2006 IEEE Nonlinear Statistical Signal Processing Workshop.
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
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.
- Subjects :
- Particle scattering
ComputingMethodologies_PATTERNRECOGNITION
Automatic control
Computational complexity theory
Computer science
Resampling
Convergence (routing)
Monte Carlo method
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Particle filter
Algorithm
Auxiliary particle filter
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2006 IEEE Nonlinear Statistical Signal Processing Workshop
- Accession number :
- edsair.doi...........53afd4b03fa853d2adfc3244b2824f03
- Full Text :
- https://doi.org/10.1109/nsspw.2006.4378824