[1]王忠勇,冯卫娜..一种基于粒子滤波的非线性系统参数和状态联合估计方法[J].郑州大学学报(工学版),2010,31(02):96.
　WANG Zhongyong,FENG Weina.Combined Estimation Method of Parameter and State for Nonlinear SystemsBased on Particle Filter[J].Journal of Zhengzhou University (Engineering Science),2010,31(02):96.
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一种基于粒子滤波的非线性系统参数和状态联合估计方法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
31卷
期数:
2010年02期
页码:
96
栏目:
出版日期:
2010-02-02

文章信息/Info

Title:
Combined Estimation Method of Parameter and State for Nonlinear SystemsBased on Particle Filter
作者:
王忠勇; 冯卫娜.
郑州大学,信息工程学院,河南,郑州,450001, 郑州大学,信息工程学院,河南,郑州,450001
Author(s):
WANG Zhongyong; FENG Weina
School of Information Engineering，Zhengzhou University，Zhengzhou 450001，China
关键词:
粒子滤波;  非线性系统;  核平滑收缩;  贝塔分布
Keywords:
article filtering; nonlinear system; kernel smoothing contraction; beta distribution
文献标志码:
A
摘要:
提出了一种新的基于粒子滤波的非线性系统参数和状态联合估计方法.该算法利用粒子滤波方法,结合核平滑收缩技术,同时采用标准贝塔分布代替传统的高斯分布,来拟合系统未知参数的后验分布,最终实现非线性系统中参数的迭代估计,仿真结果表明,该算法提高了未知参数和状态的估计精度,在估计的收敛性方面也有明显的改善.
Abstract:
A new combined estimation method of parameter and state for nonlinear systems based on particlefilter is proposed．The algorithm uses particle filter methods，combined with the kernel smoothing contractionmethod，replaces the traditional use of the Gaussian distribution with the standard beta distribution to fit theposteriori distribution of the unknown parameter of the system，in order to achieve the iteration of the parame—ter estimation of the nonlinear system．Simulation experiment results show that the algorithm improves the esti-mation accuracy of the the state and the unknown parameter，and the convergence of the estimation has alsobeen significantly improved．

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更新日期/Last Update: 1900-01-01