[author_cn_name].[cn_title][J].空军工程大学学报:自然科学版,[year_id],[volume]([issue]):[start_page]-[end_page] 基于变分贝叶斯估计方法的双尺度自适应Kalman滤波-Double Scale Adaptive Kalman Filter Based on Variational Bayesian Estimation Approach
文章摘要
吴俊峰1,徐嵩2.基于变分贝叶斯估计方法的双尺度自适应Kalman滤波[J].空军工程大学学报:自然科学版,2019,20(2):79-85
基于变分贝叶斯估计方法的双尺度自适应Kalman滤波
Double Scale Adaptive Kalman Filter Based on Variational Bayesian Estimation Approach
  
DOI:10.3969/j.issn.1009-3516.2019.02.012
中文关键词: 自适应Kalman滤波  变分贝叶斯方法  双尺度估计  启发式算法
英文关键词: adaptive Kalman filter  variational Bayesian approach  double scale estimation  heuristic algorithm
基金项目:国家自然科学基金(61772416);陕西省自然科学基础研究计划(2016JQ6065);陕西省教育厅重点实验室项目(17JS098);陕西省教育厅基础研究计划(15JK1535)
作者单位
吴俊峰1,徐嵩2 1.西安理工大学,西安,7100482.95910部队,甘肃酒泉,735018 
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中文摘要:
      针对Kalman滤波在对敌目标估计应用中遇到的量测和过程噪声均未知且时变的情况,提出了一种利用变分贝叶斯估计的双尺度自适应滤波方法。解决了2个关键问题:一是针对量测和过程噪声协方差的共轭后验分布提出了相对转移概率指标,设计了启发式的自适应噪声估计窗口,实现了稳态精度和时变响应性能的综合提升,能适应敌方目标机动性高且统计特性变化快的特点;二是设计了在不同时间尺度上估计过程噪声和量测噪声的协方差方法,解决了在同一时间尺度上使协方差估计值发生严重偏差且增大滤波误差的问题。仿真表明,所提方法能快速跟踪目标状态噪声统计特性的变化并保证估计精度。
英文摘要:
      In consideration of the problem in applying Kalman filter when time varying noise covariance matric of measurement and process are neither known, a new adaptive filter was purposed by Variational Bayesian(VB) approach. This filter overcame two key problems as following: first, relative transfer probability was proposed as realizing to promote the performances of steady state precision and dynamic respond simultaneously, by designing the heuristic adaptive window for noise estimation, according to the conjugate posterior distribution of measurement and process noise; second, the serious offset of the estimation value of noise covariance matric under single time scale was notable reduced by designing the approach which estimated the covariance matric under double time scales. The simulations proved that this method could track the noise statistics feature quickly without losing estimation precision.
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