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A Hierarchical Resampling Algorithm with Adaptive Interval for Particle Filter

원문정보

초록

영어

In this article, we present an improved resampling algorithm for particle filtering, which is based on partial resampling and residual resampling. This algorithm provides an approach to selectively carry out hierarchical resampling operations on three sets of particles divided by large, medium and small weights, and especially to do skip resampling for partial small particles with an adaptive interval M. Simulation results verify that the proposed algorithm could reduce the depletion problem, maintain a good diversity of particles and improve the accuracy of PF performance.

목차

Abstract
 1. Introduction
 2. Fundamentals of Particle Filtering
 3. Resampling Scheme and the Improved Algorithms
  3.1. Resampling Schemes
  3.2. Three Definitions for the Improved Partial Resampling Scheme
 4. Simulation and Results
 5. Conclusions
 References

저자정보

  • Xiaohui-Zeng School of Communication Engineering, Chengdu University of Information and Technology, Chengdu, China, School of Automation Engineering, UESTC, Chengdu, China
  • Yibing-Shi School of Automation Engineering, UESTC, Chengdu, China
  • Yi-Lian Motorola (China) Solutions, Chengdu, China

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