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非线性系统测量数据丢失时的一种粒子滤波器算法
引用本文:李雄杰,周东华.非线性系统测量数据丢失时的一种粒子滤波器算法[J].兵工学报,2009,30(10):1405-1408.
作者姓名:李雄杰  周东华
作者单位:浙江工商职业技术学院,机电工程系,浙江,宁波,315012;清华大学,自动化系,北京,100084;清华大学,自动化系,北京,100084
基金项目:国家自然科学基金项目 
摘    要:针对在工程实践中发生的测量数据随机丢失情况,提出了一种应用于非线性系统的滤波方法,该方法将基于序贯重要性采样的粒子滤波器应用于非线性、非高斯系统状态的在线状态估计。首先将测量数据丢失描述成满足一定条件概率分布的二元开关序列;然后基于似然函数设计方法,设计出测量数据丢失时的粒子滤波器算法;最后用本文方法对倒立摆系统状态估计进行了仿真。仿真实验表明,测量数据丢失时的粒子滤波器算法是有效的。

关 键 词:自动控制技术  粒子滤波器  测量数据丢失  非线性系统  状态估计

A Particle Filter Algorithm in the Presence of Missing Measurements for a Nonlinear System
LI Xiong-jie,ZHOU Dong-hua.A Particle Filter Algorithm in the Presence of Missing Measurements for a Nonlinear System[J].Acta Armamentarii,2009,30(10):1405-1408.
Authors:LI Xiong-jie  ZHOU Dong-hua
Affiliation:1. Department of Mechanical & Electrical Engineering, Zhejiang Business Technology Institute, Ningbo 305012, Zhejiang, Cnina; 2. Department of Automation, Tsinghua University,Beijing 100084, China
Abstract:Aimed at the case that sensor data may be missing randomly in practice, a filtering approach was proposed for the nonlinear systems, which applies a particle filter based on sequential importance sampling to the on-line state estimation of non-Gauss and nonlinear systems. The missing sensor data were described as a binary switching sequence which satisfies a certain conditional probability distribution; a particle filter algorithm in the presence of missing sensor data was designed based on likelihood function; the state estimation of a upside-down pendulum system was simulated by the proposed approach. The simulated results show the effectiveness of the proposed algorithm.
Keywords:automatic control technology  particle filter  missing measurements  nonlinear system  state estimation
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