摘要
针对单一定位系统无法得到连续、稳定可靠的导航信息的问题,将全球卫星导航系统(GNSS)与捷联惯性导航系统(SINS)进行组合,并利用扩展卡尔曼滤波(EKF)算法对这两种导航系统的定位信息进行融合,以获得更加稳定、精确的定位结果。将GNSS与SINS组合,可以弥补GNSS卫星信号失锁、数据更新频率低、无法获得姿态信息以及SINS定位误差累积等单导航系统定位的不足。通过车载实验采集定位数据,并分别进行SINS单独导航及GNSS/SINS组合导航解算,由实验结果可以看出,与SINS单独导航相比,GNSS/SINS组合导航系统的定位误差能快速收敛,并保持较高的精度,其中位置误差精度达到厘米级,速度的最大误差大约在0.1m·s-1以内,姿态的最大误差大约在0.2°以内。
In order to solve the problem that a single positioning system cannot obtain continuous,stable and reliable navigation information,global navigation satellite system(GNSS)and strapdown inertial navigation system(SINS)were integrated by the extended Kalman filter(EKF)algorithm to obtain more stable and accurate positioning results in this paper.By combining GNSS with SINS together,the defects of the single navigation systems positioning,such as satellite signal loss,low data update frequency,inability to obtain attitude information of GNSS and positioning error accumulation of SINS,were compensated.In this paper,the positioning data was collected by vehicle experiments,and SINS single navigation and GNSS/SINS integrated navigation solution were performed separately.It can be seen from the experimental results that with the position error accuracy reaching the centimeter level,the maximum speed error approximately within 0.1 m·s-1,and the maximum attitude error approximately within 0.2°,the positioning error of GNSS/SINS integrated navigation system can converge more quickly and maintain higher precision than that of SINS single navigation.
作者
杨晓明
王胜利
王海霞
陈云
吕英俊
YANG Xiaoming;WANG Shengli;WANG Haixia;CHEN Yun;LU Yingjun(Shandong Provincial Key Laboratory of Robotics and Intelligent Technology,Shandong University of Science and Technology,Qingdao,Shandong 266590,China;Institute of Ocean Engineering,Shandong University of Science and Technology,Qingdao,Shandong 266590,China;Department of Electrical Engineering&Information Technology,Shandong University of Science and Technology,Jinan,Shandong 250031,China)
出处
《山东科技大学学报(自然科学版)》
CAS
北大核心
2019年第6期114-122,共9页
Journal of Shandong University of Science and Technology(Natural Science)
基金
国家自然科学基金项目(61773245,61603068,61806113)
山东省重点研发计划项目(2018GGX101053)
泰山学者计划