Publication Date:
2018-11-06
Description:
Traditional resampling methods in particle filter suffer from the disadvantage of the low filtering accuracy, the severe fluctuation of effective sample size (ESS) and the great influence of parameter setting. A particle filter algorithm based on chopthin resampling is proposed in this paper. Traditional resampling methods produce a set of equally weighted particles and only occur when ESS below a threshold. In contrast to this, the proposed algorithm enforces an upper bound on the ratio between the weights and can be implemented in every step. Simulation shows that the new method outperforms traditional resampling methods in filtering accuracy, ESS stability and computational efficiency, especially when sample size or observation noise is small.
Print ISSN:
1757-8981
Electronic ISSN:
1757-899X
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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