智能系统学报2012，Vol.7Issue(4)：345-351,7.DOI:10.3969/j.issn.1673-4785.201203001
自适应扩维UKF算法在SINS/GPS组合导航系统中的应用
An adaptive augmented unscented Kalman filter with applications in a SINS/GPS integrated navigation system
摘要
Abstract
Because an adaptive fading Kalman filter cannot he applied to nonlinear systems, an augmented unscent-ed Kalman filter (AUKF) based on an adaptive fading matrix (AFM) was proposed in this paper. The AFM-AUKF algorithm was implemented by first calculating the adaptive fading matrix, and then using the unscented transforma-tion to estimate the posterior mean and covariance of the state of a nonlinear system, so as to effectively solve the filtering problem. In order to solve the problem of nonlinear state estimation in a low-cost integrated navigation sys-tem , a filter fault-tolerant experiment and a system noise mutation experiment were designed and implemented, re-spectively. The experimental results prove that the algorithm enhances the robustness of the filter when the system model is uncertain, improves the accuracy of the filter, and has a strong fault-tolerant ability.关键词
扩维UKF/自适应渐消矩阵/组合导航/非线性滤波Key words
augmented unscented Kalman filter/adaptive fading matrix/integrated navigation/nonlinear filter分类
信息技术与安全科学引用本文复制引用
孙尧,马涛,高延滨,王璐..自适应扩维UKF算法在SINS/GPS组合导航系统中的应用[J].智能系统学报,2012,7(4):345-351,7.基金项目
国家自然科学基金资助项目(50909025/E091002) （50909025/E091002）
国际科技合作基金资助项目(2010DFR80140). （2010DFR80140）
