基于手机内置传感器的车辆组合定位方法  

Smartphone built-in sensors based vehicle integrated positioning method

作　　者：旷俭 葛雯斐 张全[1] 窦智 唐爱鹏 张小兵 牛小骥[1] KUANG Jian;GE Wenfei;ZHANG Quan;DOU Zhi;TANG Aipeng;ZHANG Xiaobing;NIU Xiaoji(GNSS Research Center,Wuhan University,Wuhan 430079,China;AutoNavi Software Technology Co.,Ltd,Beijing 100020,China)

机构地区：[1]武汉大学卫星导航定位技术研究中心,武汉430079 [2]高德软件技术有限公司,北京100020

出　　处：《中国惯性技术学报》2020年第6期701-708,共8页Journal of Chinese Inertial Technology

基　　金：国家重点研发计划项目(No.2016YFB0502202);国家自然基金面上项目(41974024,41904019)。

摘　　要：面向基于手机内置传感器的车辆定位问题,设计了一种GNSS、陀螺仪、加速度计和磁力计等多种传感器组合定位算法。以惯性导航系统(INS)为桥梁,使用扩展卡尔曼滤波(EKF)框架融合其它定位源和约束信息。量测更新信息包括GNSS位置、零速、零航向角速率、磁场航向角变化量、车辆运动约束以及车辆前向速度预测模型等。其中,手机朝向与车辆朝向的夹角以及惯性传感器测量中心到车辆后轮中心的杆臂作为增广待估参数,以便充分发挥车辆运动约束的效果。另外,为了发挥数据后处理的优势,在滤波处理完成后,反向平滑被用于进一步提升系统的定位精度。基于国际比赛公开数据集的测试结果表明,所提出的算法能够有效地融合不同传感器和车辆运动约束信息,即使在卫星信号受到干扰或者遮挡的情况下,也能够在短时间内(例如400秒)输出稳定、可靠的定位结果。在第七届室内定位与室内导航国际会议(IPIN2020)-室内定位比赛的赛题六“基于智能手机的车辆定位”中,所提出的算法以定位精度优于7 m(75%概率)的成绩获得该赛题的冠军。To meet the vehicle positioning requirement using the built-in sensor of smart phone,a positioning algorithm is designed integrating GNSS,gyroscope,accelerometer and magnetometer.The Inertial Navigation System(INS)is used as a bridge,and the Extended Kalman Filter(EKF)is used to fuse other positioning sources and constraint information.The update information includes GNSS position,zero velocity,zero heading angular rate,magnetic field heading angle variation,vehicle motion constraint and vehicle speed prediction model.Among them,the misaligned angle between smartphone and vehicle and the lever-arm from the inertial sensor to the center of the rear wheels are used as augmented states to be evaluated so as to maximized the effect of vehicle motion constraint.In addition,to take the advantages of data post-processing,backward smoothing is used to further improve the positioning accuracy of the system after the forward filtering.Test results based on the published dataset of an international competitions show that the proposed algorithm can effectively integrate different sensors in the phone and the vehicle motion constraint information,and can output stable and reliable positioning results even when the GNSS signals are interfered or blocked for short time(i.e.400 seconds).In track 6"Smartphone-based Vehicle positioning without additional equipment"of the Indoor Positioning and Indoor Navigation Conference(IPIN2020)-7th indoor positioning competition,the proposed algorithm won the championshipwith the positioning accuracy better than 7 m(75%probability).

关 键 词：智能手机 MEMS-IMU 车辆定位 GNSS 磁力计 

分 类 号：P232[天文地球—摄影测量与遥感]