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非线性非高斯秩滤波方法 被引量:2

Nonlinear and non-Guassian rank filter method
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摘要 基于秩滤波原理,提出一种非线性非高斯秩滤波方法,给出其递推过程.目前常用的非线性滤波方法有尢迹Kalman滤波和粒子滤波,无迹Kalman滤波只适用于高斯分布的情况,粒子滤波方法却存在粒子退化及重采样引起的粒子贫化问题.而非线性非高斯秩滤波方法不仅适用于常见的多元t分布、多元极值分布等非高斯分布的非线性滤波,并且计算简单、工作量小,便于工程应用.从仿真算例可以看到,该方法的滤波精度与无迹Kalman滤波和粒子滤波方法相比提高了500%以上. A nonlinear and non Guassian rank filter (RF) method based on the principle of rank filter was presented. Furthermore, its filter recursive process was also given. Un scented Kalman filter (UKF) only for Gaussian distribution and particle filter (PF) for non- Gaussian distribution were the two common nonlinear filter methods, but PF had the prob- lems of particle degeneracy, particle impoverishment caused by resampling and complicated calculation. Compared with the two methods, the proposed RF is suitable for not only Gaussian distribution but also non-Gaussian distributions such as multivariate t distributions and extreme value distributions, and RF is simple to calculate and easy to apply in engineer ing. Moreover, it has low amount of calculation. From the simulation comparisons of RF, UKF and PF in the example, the filtering accuracy of RF increased at least 500%.
作者 傅惠民 肖强 娄泰山 肖梦丽 FU Hui-min, XIAO Qiang, LOU Tai-shan, XIAO Meng-li (Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191,China)
出处 《航空动力学报》 EI CAS CSCD 北大核心 2015年第10期2318-2322,共5页 Journal of Aerospace Power
基金 国家重点基础研究发展计划(2012CB720000)
关键词 秩滤波 无迹Kalman滤波 粒子滤波 KALMAN滤波 非线性滤波 非高斯滤波 rank filter unscented Kalman filter particle filter Kalman filter nonlinear filter non-Gaussian filter
作者简介 傅惠民(1956-),男,浙江遂昌人,“长江学者”特聘教授、博士生导师,博士,从事小样本信息技术、软校准技术、数据融合方法、可靠性及滤波理论研究.
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参考文献18

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