| 基于蒙特卡洛方法的粒子滤波算法研究 |
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| 引用本文： | 李军科,张串,吴建军. 基于蒙特卡洛方法的粒子滤波算法研究[J]. 电脑与信息技术, 2008, 16(1): 49-53 |
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| 作者姓名： | 李军科 张串 吴建军 |
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| 作者单位： | 无锡商业职业技术学院;无锡商业职业技术学院 |
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| 摘 要： | 针对非线性、非高斯问题,文章详细分析了贝叶斯滤波的原理及其进展.采用近似线性及高斯假设处理,传统的卡尔曼滤波提供了一种很好的解决方案.但是,真实世界的非线性、非高斯问题存在,使得人们得不寻找一种更好的最优滤波方法.基于随机滤波理论、贝叶斯统计量和蒙特卡洛方法的粒子滤波理论迅速发展,并广泛应用到数字通信、目标跟踪、计算机视觉和机器故障诊断领域.
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| 关 键 词： | 卡尔曼滤波 粒子滤波 序列蒙特卡洛 贝叶斯滤波 重要性采样 |
| 文章编号： | 1005-1228（2008）01-0049-05 |
| 收稿时间： | 2007-09-18 |
| 修稿时间： | 2007-11-24 |
Study of Particle Filter Algorithm Based on Monte Carlo Methods |
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| LI Jun-ke,ZHANG Chuan,WU Jian-jun. Study of Particle Filter Algorithm Based on Monte Carlo Methods[J]. Computer and Information Technology, 2008, 16(1): 49-53 |
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| Authors: | LI Jun-ke ZHANG Chuan WU Jian-jun |
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| Affiliation: | LI Jun-ke1,ZHANG Chuan2,WU Jian-jun1 (1.Electronic Engineering Department,Wuxi Institute of Commerce,Wuxi,Jiangsu 214153,China,2.Shanghai Acoustics LAB,Institute of Acoustics,Chinese Academy of Sciences,Shanghai 200032,China) |
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| Abstract: | This paper analyzes the Bayesian theory and its development in detail ,focusing on the nonlinear or non- Gaussian problems. The Kalman filter provides a classic approach to linear-Gaussian estimation problem. However,due to the nonlinear or non-Gaussian in real world, people have to search for a better kind of filter. Based on stochastic filtering theory, Bayesian theory and Monte Carlo methods ,the particle filter theory is developing more and more, and applies in the fields such as digital communication, target tracking, computer vision and fault detection. |
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| Keywords: | Karlman filtering , particle filtering sequential Monte Carlo Bayesian filtering , Important sampling |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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