| 改进权值计算的EPF算法及在目标跟踪中的应用 |
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| 引用本文： | 王秋平,周原,康顺,左玲.改进权值计算的EPF算法及在目标跟踪中的应用[J].电光与控制,2011,18(4):10-12,25. |
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| 作者姓名： | 王秋平 周原 康顺 左玲 |
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| 作者单位： | 东北电力大学自动化工程学院,吉林,吉林,132012 |
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| 基金项目： | 东北电力大学博士基金，吉林省教育厅项目，吉林市科技发展计划资助项目 |
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| 摘 要： | 扩展卡尔曼粒子滤波(EPF)在预测阶段通过EKF选取重要性函数而优化了粒子选取,但是传统EPF算法中粒子权值一般是通过正态分布的概率密度函数计算的.此方法没有突出不同噪声粒子的权值差别,在计算中引入了较大的相对误差.通过在更新阶段对权值计算所依赖的概率密度函数做出改进,得到改进的EPF算法.同时采用实际目标跟踪数据进行...
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| 关 键 词： | 目标跟踪 粒子滤波(PF) EPF 概率密度函数 权值计算 正态分布 反比例函数 |
An EPF Algorithm with Improved Particle Weight Calculation and Its Application in Tracking System |
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| WANG Qiuping,ZHOU Yuan,KANG Shun,ZUO Ling.An EPF Algorithm with Improved Particle Weight Calculation and Its Application in Tracking System[J].Electronics Optics & Control,2011,18(4):10-12,25. |
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| Authors: | WANG Qiuping ZHOU Yuan KANG Shun ZUO Ling |
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| Affiliation: | WANG Qiuping,ZHOU Yuan,KANG Shun,ZUO Ling(School of Automation Engineering,Northeast Dianli University,Jilin 132012,China) |
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| Abstract: | Extended Particle Filter(EPF) determines the importance function based on EKF in the predicting stage and optimizes the choice of particles.In traditional EPF algorithm,however,the particle weight is usually obtained using normal distribution function as probability density function.The weight differences among particles with different noises are not emphasized,which may bring large relative error in the calculation.We made improvement to the probability density function upon which the weight calculation is... |
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| Keywords: | EPF |
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