DocumentCode :
536537
Title :
Study on the Adaptive Partial Systematic Resampling Algorithm of Particle Filter
Author :
Liu, Wenjing ; Yu, Jinxia ; Xu, Jingmin
Author_Institution :
Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
fYear :
2010
fDate :
7-9 Nov. 2010
Firstpage :
1
Lastpage :
4
Abstract :
Sample degeneracy is a major problem of particle filter which is based on the sequential importance sampling. In order to solve this problem, the resampling algorithm is introduced in particle filter. Regular resampling algorithm can solve the sample degradation, but it easily lead to sample depletion and increase the computing complexity. The adaptive partial systematic resampling (APSR) algorithm adjusts the resampling time adaptively, before the resampling, classified the particles according to the weight, resampling is carries on the minority particles, The simulation result indicated that it increase the particle diversity and reduces the computation time.
Keywords :
computational complexity; particle filtering (numerical methods); sampling methods; adaptive partial systematic resampling algorithm; computing complexity; particle filter; sample degeneracy; sample degradation; sequential importance sampling; Adaptive systems; Bayesian methods; Classification algorithms; Mathematical model; Monte Carlo methods; Particle filters; Systematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
Type :
conf
DOI :
10.1109/ICEEE.2010.5660244
Filename :
5660244
Link To Document :
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