Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (11): 11-15.

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New nonlinear filter algorithm for high precision

LI Yuchen1,2, LI Zhanming1,2   

  1. 1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
    2.The Key Laboratory of Advanced Control of Industrial Processes of Gansu Province, Lanzhou 730050, China
  • Online:2012-04-11 Published:2012-04-16



  1. 1.兰州理工大学 电气工程与信息工程学院,兰州 730050
    2.甘肃省工业过程先进控制重点实验室,兰州 730050

Abstract: A new particle filter is proposed for the on-line estimation problem of non-Gauss nonlinear systems. The new algorithm corrects the integral points of quadrature Kalman filter on line and uses pruning quadrature Kalman filter to produce optimization proposal distribution function, overcomes the particle degeneration phenomenon well as measured with high accuracy into the latest information. Theoretical analysis and experiments show that the proposed algorithm is a new kind of particle filter algorithm for high precision.

Key words: particle filter, important density function, quadrature Kalman filter, pruning factor

摘要: 针对非线性、非高斯系统状态的在线估计问题,提出了一种新的高精度粒子滤波算法。该算法通过引入积分修正因子,对积分卡尔曼滤波器的积分点进行在线修正,并采用修正后的积分卡尔曼滤波产生优选的建议分布函数,由于高精度地融入最新量测信息,一定程度上克服了权值退化问题。仿真实验表明,新算法具有较高的滤波精度,是一种有效的非线性滤波算法。

关键词: 粒子滤波, 重要性密度函数, 积分卡尔曼滤波, 修正因子