计算机工程与应用2017，Vol.53Issue(7)：21-29,53,10.DOI:10.3778/j.issn.1002-8331.1611-0038
基于Huber的鲁棒高阶容积卡尔曼滤波算法
Huber-based robust high-degree cubature Kalman filter algrithm
摘要
Abstract
To further improve the filtering accuracy and robustness of high-degree cubature Kalman filter when the ran-dom variable within non-Gaussian distribution, this paper presents a new filtering algorithm named Huber-based robust high-degree cubature Kalman filter algorithm. It is interpreted that the basic idea of Huber method acting on Kalman filter can be described as truncating the average from the perspective of recursive Bayesian approximation estimation. The observation vector is preprocessed by Huber method within the framework of the existed filtering, then the normal measure-ment update is implemented by using the preprocessed observation information, the robustness of the HCKF algorithm is realized consequently. The new method without approximating nonlinear measurements model by using the statistical lin-ear regression model, the preponderance of high-degree cubature transform is fully used and the high precision is main-tained while the robustness is ensured. Simulations in the context of univariate non-stationary growth model and the prob-lem of reentry vehicle tracking demonstrate that the new method has superior performance in robustness and efficiency.关键词
Huber方法/高斯滤波/高阶容积准则/鲁棒性/滤波精度Key words
Huber method/Gaussian filter/high-degree cubature rule/robustness/filtering accuracy分类
信息技术与安全科学引用本文复制引用
秦康,董新民,陈勇..基于Huber的鲁棒高阶容积卡尔曼滤波算法[J].计算机工程与应用,2017,53(7):21-29,53,10.基金项目
国家自然科学基金(No.61304120,No.61473307,No.61603411) （No.61304120,No.61473307,No.61603411）
民口973项目(No.2015CB755802) （No.2015CB755802）
航空科学基金(No.20155896026). （No.20155896026）
