摘要
为了解决量测方程线性化及普通卡尔曼滤波数值稳定性对车载航位推算系统滤波结果的影响,给出了车载航位推算系统的基于U D分解的自适应迭代滤波算法,并将这一算法与车载航位推算系统的迭代型自适应推广卡尔曼滤波算法及简单航位推算进行了比较。计算机仿真结果表明:新算法能够有效地提高车载航位推算系统的定位精度及数值稳定性。
For dealing with affect caused by linearization of the surveying equation and the bad numerical stability of Kalman filter,U-D factorization-based adaptive extended iterative filter model of dead-reckoning (DR) system for land vehicle navigation and its filtering algorithm are proposed,the new algorithm also being compared with iterative version of adaptive extended Kalman filter algorithm and sample dead reckoning algorithm.The computer simulation results show that the positioning accuracy and numerical stability of the system can be remarkable improved by this algorithm.
出处
《传感器技术》
CSCD
北大核心
2004年第12期62-65,共4页
Journal of Transducer Technology
基金
国家自然科学基金资助项目(49871071)
关键词
车辆导航
U-D分解
卡尔曼滤波
迭代
航位推算
land vehicle navigation
U-D factorization
Kalman filter
iterative
DR(dead-reckoning)
