摘要
针对车载组合导航信息融合的高精度、高可靠性等要求,提出了一种组合导航的自适应集中滤波算法.该算法的主要思想是:以判别观测数据中的野值存在与否为算法切换条件,存在野值时采用改进的增益矩阵滤波处理方法,不存在野值时则采用模糊自适应集中滤波方法.将此方法用于SINS/GPS车载组合导航系统,实验表明,采用的这种自适应滤波方法,能够有效抑制滤波发散,滤波精度和收敛速度优于常规集中滤波,是一种有效的车载组合导航算法.
A new adaptive central filter used in integrated navigation system of land vehicle is presented to achieve the＇ high guidance-precision and anti-jamming. The main idea is using the fault datum as switching condition. While fault datum exists, choosing improved gain matrix of the Kalman filter approach; other- wise choosing a fuzzy adaptive Kalman filter approach. Experiment results show that, when this approach is used in SINS/GPS integrated navigation systems, filtering precision and converging speed are better than those of general Kalman filter.
出处
《重庆工学院学报（自然科学版）》
2008年第3期104-107,共4页
Journal of Chongqing Institute of Technology
基金
重庆市教委基础研究项目(KJ070605)
关键词
车载组合导航
信息融合
模糊推理
卡尔曼滤波
integrated navigation system
information fusion
fuzzy reasoning
central Kalman filter
