车载GPS/DR组合导航系统的数据融合方法研究  

Research on Data Fusion Method of Vehicle GPS /DR Integrated Navigation System

作　　者：张丽平[1] 李环[1] 

机构地区：[1]沈阳理工大学信息科学与工程学院,辽宁沈阳110159

出　　处：《沈阳理工大学学报》2014年第1期13-17,40,共6页Journal of Shenyang Ligong University

摘　　要：GPS/DR组合导航系统是非线性的,扩展卡尔曼滤波(EKF)可以利用线性化技巧将其转化为线性滤波问题,但这一过程会使得滤波结果出现很大误差。针对这一问题,将改进的粒子滤波方法(UPF),即将无迹卡尔曼滤波(UKF)与粒子滤波(PF)相结合,应用到GPS/DR组合导航系统中,避免了EKF的线性化近似过程,同时优化了PF算法,提高了定位精度。实验结果表明,与EKF和PF算法相比,UPF算法具有更高的鲁棒性和更好的定位效果。GPS/DR integrated navigation system is a nonlinear system, which leads to a big error in realizing system linearization by using the extended Kalman filter （EKF）. Aiming at solving the problem,the improved particle filter algorithm （UPF） combining the unscent- ed Kalman filter （UKF） and particle filter （PF） is applied to the GPS/DR integrated navi- gation system. It not only avoids the linear approximation of EKF, but also optimizes the PF algorithm and improves the positioning accuracy. Experimental results show that, compared with the EKF algorithm and PF algorithm, UPF algorithm has higher robustness and better positioning effect.

关 键 词：GPS DR组合导航 扩展Kalman滤波 无迹Kalman滤波 粒子滤波 

分 类 号：TN967.2[电子电信—信号与信息处理]