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基于自适应衰减系数的VB-AKF算法

发表时间:2014-04-30  浏览量:1622  下载量:516
全部作者: 黄建军,刘杰
作者单位: 深圳大学信息工程学院
摘 要: 提出了一种基于衰减系数自适应的变分贝叶斯自适应卡尔曼滤波(variational Bayesian based adaptive Kalman filter,VB-AKF)算法。该算法利用量测数据精度等级对衰减系数进行自适应调整,解决了VB-AKF算法事先设定的衰减系数不能完全适应量测噪声方差动态变化的问题。仿真结果表明,该算法能够快速有效地估计出动态变化的量测噪声方差,并且能够有效地实现数据滤波。
关 键 词: 信息处理技术;变分贝叶斯自适应卡尔曼滤波;精度等级;自适应衰减系数;量测噪声方差估计
Title: A VB-AKF algorithm based on adaptive attenuation parameter
Author: HUANG Jianjun, LIU Jie
Organization: College of Information Engineering, Shenzhen University
Abstract: An adaptive attenuation parameter is introduced to adapt the dynamics of variational Bayesian based adaptive Kalman filter (VB-AKF). The proposed algorithm adjusts adaptively the attenuation parameter by the accuracy category of measurement data. Thus the problem that the presetting constant attenuation parameter in VB-AKF can not fully adapt to the measurement noise variance dynamics is solved. Simulation results show that the proposed algorithm can estimate the dynamic varying measurement noise variance effectively and efficiently, and achieve an effective data filtering.
Key words: information processing technology; variational Bayesian base adaptive Kalman filter; accuracy category; adaptive attenuation parameter; estimation of measurement noise variance
发表期数: 2014年4月第8期
引用格式: 黄建军,刘杰. 基于自适应衰减系数的VB-AKF算法[J]. 中国科技论文在线精品论文,2014,7(8):755-759.
 
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