A Sample Size Adaptation Scheme for Particle Filter
Particle filter is a Monte Carlo method to monitor dynamic systems, which non-parametrically approximates probabilistic distribution using weighted samples. Particle filters have been widely used in various fields such as robotics, visual tracking, etc. A key issue for fast implementation of particle filter is how to determine the sample size (particle number) according the sample based distribution. The paper presents a sample size adaptation scheme for particle filters. The key idea is to adjust sample size according to the distance of two sample-based distributions with different sample scale. The method is testified on nonlinear system estimation problem.
Particle Filter Sample Size Adaptive
Zhuohua Duan
School of Computer Science, Shaoguan University, Shaoguan 512005
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
3024-3028
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）