计算机科学与应用

Vol.1 No.3 (December 2011)

粒子滤波算法的优化与改进
Optimization of the Particle Filter Algorithm

 

作者:

梁磊 , 曹洁 , 赵丽丽

 

关键词:

粒子滤波粒子群优化算法遗传算法粒子退化粒子贫化Particle Filter Particle Swarm Optimization Genetic Algorithm Particle Degeneracy Particle Impoverishment

 

摘要:

本文对粒子滤波的基本概念与算法原理进行了详细的介绍,分析了粒子滤波所存在的粒子退化问题和重采样所导致的粒子匮乏问题,以及目前针对这两个问题所提出的粒子滤波的优化算法。最后,给出了粒子滤波与智能算法相结合的方法。通过对粒子滤波与智能算法的结合,可以更有效的克服粒子滤波的缺点,仿真结果表明,通过智能算法优化的粒子滤波的滤波性能优于传统的粒子滤波优化算法。

In this paper, two problems were explicated by the detailed presentation of basic concepts and prin- ciples of the particle filter algorithm. One is particle impoverishment which dues to re-sampling, and another is particle degeneracy. To overcome these problems, existed methods of particle filter optimization are analy- zed. Finally, this paper presented a method that combine particle filter with intelligent algorithm, the combi- nation algorithm can overcome the shortcomings of particle filter effectively. Simulation results show that it is superior to the traditional particle filter optimization algorithm.

文章引用:

梁磊 , 曹洁 , 赵丽丽 (2011) 粒子滤波算法的优化与改进。 计算机科学与应用, 1, 112-117. doi: 10.12677/csa.2011.13023

 

分享
Top