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基于变尺度变换减少Sigma点的粒子滤波算法研究

赵光琼 陈绍刚 付奎 唐忠樑 贺威

赵光琼, 陈绍刚, 付奎, 唐忠樑, 贺威. 基于变尺度变换减少Sigma点的粒子滤波算法研究. 自动化学报, 2015, 41(7): 1350-1355. doi: 10.16383/j.aas.2015.c140833
引用本文: 赵光琼, 陈绍刚, 付奎, 唐忠樑, 贺威. 基于变尺度变换减少Sigma点的粒子滤波算法研究. 自动化学报, 2015, 41(7): 1350-1355. doi: 10.16383/j.aas.2015.c140833
ZHAO Guang-Qiong, CHEN Shao-Gang, FU Kui, TANG Zhong-Liang, HE Wei. A Particle Filter Algorithm Based on Scaled UKF with Reduced Sigma Points. ACTA AUTOMATICA SINICA, 2015, 41(7): 1350-1355. doi: 10.16383/j.aas.2015.c140833
Citation: ZHAO Guang-Qiong, CHEN Shao-Gang, FU Kui, TANG Zhong-Liang, HE Wei. A Particle Filter Algorithm Based on Scaled UKF with Reduced Sigma Points. ACTA AUTOMATICA SINICA, 2015, 41(7): 1350-1355. doi: 10.16383/j.aas.2015.c140833

基于变尺度变换减少Sigma点的粒子滤波算法研究

doi: 10.16383/j.aas.2015.c140833
基金项目: 

国家重点基础研究发展计划(973计划) (2014CB744206)资助

详细信息
    作者简介:

    赵光琼电子科技大学数学科学学院硕士研究生. 主要研究方向为控制论. E-mail: zhaoguangqiong.math@gmail.com

A Particle Filter Algorithm Based on Scaled UKF with Reduced Sigma Points

Funds: 

Supported by National Basic Research Program of China (973 Program) (2014CB744206)

  • 摘要: 为了减少传统无味粒子滤波(Unscented particle filter, UPF) 算法的计算负担, 提出了最小斜度单形无味转换(Minimal skew simplex UT, MSSUT) 方法, 这种方法是用最小斜度无味卡尔曼滤波来产生粒子的重要性函数. 它不仅能够扩大重要性分布与系统状态的后验概率密度的重叠性, 而且能够通过减少Sigma 点来减少计算负担. 但是, 随着状态空间维数的增加, Sigma 点集的覆盖半径增大, 导致了Sigma 点集的聚集性变差. 辅助随机变量变尺度无味变换(Auxiliary random variable formulation of the scaled unscented transformation, ASUT) 能够克服Sigma 点集分布扩展的缺点. 所以, 提出了一种高维空间中改进的变尺度最小斜度无味粒子滤波(Scaled minimal skew simplex unscented particle filter, SMSSUPF) 算法. 仿真结果表明: 在高维状态空间中, 与传统的无味粒子滤波(UPF) 相比, 计算复杂度和计算负担显著减少. 与最小斜度无味粒子滤波(Minimal skew simplex unscented particle filter, MSSUPF) 相比, SMSSUPF 减少了系统噪声方差和测量噪声方差所带来的估计误差.
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出版历程
  • 收稿日期:  2014-12-03
  • 修回日期:  2015-03-03
  • 刊出日期:  2015-07-20

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