An improved particle filter based on genetic resampling

DOI

10.2991/amcce-15.2015.125How to use a DOI?

Keywords

particle filter; genetic algorithm; sample impoverishment; resampling

Abstract

The resampling of particle filter algorithm causes sample impoverishment and results in the loss of diversity. An improved particle filter algorithm is proposed by combining genetic algorithm and PF. First of all, particles are selected according to the probability with the principle of selection in genetic algorithm which make particles with larger weights to be selected more likely , and the proposed algorithm can guide the entire process to the direction of evolution. Crossover and mutation are adopted to replace the strategy of resampling which simply copy particles with high weight, delete particles with low weight and implement the particle update and optimization. Finally, the simulation experiments show that the proposed algorithm can more effectively improve the diversity of particles.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bin Zhao
AU  - Jian-wang Hu
AU  - Bing Ji
PY  - 2015/04
DA  - 2015/04
TI  - An improved particle filter based on genetic resampling
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 1353
EP  - 1358
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.125
DO  - 10.2991/amcce-15.2015.125
ID  - Zhao2015/04
ER  -