摘要
针对陆地车辆导航应用,基于速度特性建立了机体系约束用以提高卫星导航系统(GNSS)/微硅机械(MEMS)惯性组合导航系统的性能.该约束将与车体运动方向相垂直的平面上的线速度近似为0,从而增加了组合系统的扩展卡尔曼滤波时间上连续的两维虚拟观测量,卫星信号失效时可保持滤波器的量测更新,当无外部观测量且车辆处于动态情况下,滤波可持续估计与反馈.车载实验表明,组合系统在卫星信号失效30s时,采用该算法可以将系统的定位精度提高约75%,姿态精度及速度精度也有相应的提高.
For global navigation satellite system（GNSS） and micro-electro mechanical system （MEMS） inertial navigation system （INS） integrated system in land vehicle application, a particular constraint based on features of a vehicle＇s motion is setup on its body frame to improve the system performance. Body frame constraint limits the velocities along the plane perpendicular to the vehicle＇s moving direction to approximate zero, which accordingly introduces couple of additionally virtual measurements into the extended Kalman filter （EKF） that is typically applied for two systems fusion. Thanks to those virtual measurements, the EKF is able to keep its measurement updates even over GNSS signal outage period. The filter continuously produces error estimations and feedbacks during the absence of external observables from GNSS, whatever the vehicle＇s dynamics is. The field test indicates that the system accuracy of positioning can be improved by 75% over 30 s GNSS outages and the accuracy of attitude and velocity is improved as well.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2013年第5期510-515,共6页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61173076)
关键词
MEMS惯性导航系统
卫星导航
组合导航
机体系约束
扩展卡尔曼滤波
MEMS intertial navigation system（INS）
global navigation satellite system （GNSS）
integrated navigation
body frame constraint
extended Kalman filter （EKF）
