城市环境下智能手机车载GNSS/MEMSIMU紧组合定位算法

Smartphone GNSS/MEMS IMU Tightly-Coupled Integration Positioning Method for Vehicular Navigation in Urban Conditions

针对城市环境下卫星信号遮挡严重,智能手机全球导航卫星系统(global navigation satellite system,GNSS)定位难以保证连续性和可靠性的问题,提出了一种基于智能手机内置传感器数据的GNSS/微机械惯性测量单元(micro-electro-mechanical system inertialmeasurem entunit,MEMSIMU)紧组合车载导航算法。算法使用惯性导航系统机械编排进行时间更新,在车辆运动模型约束的基础上,使用伪距、多普勒频移和载波相位时间差分计算的航向角作为观测值进行测量更新。采用3部不同型号的智能手机进行车载试验分析,结果表明:城市场景下紧组合滤波定位算法平面位置精度统计约为5~6m,高程方向约为5m,且在GNSS信号失锁的隧道场景下具有短时间推算功能。该算法受GNSS观测条件的影响较小,大幅提升了城市复杂环境下智能手机车载定位的连续性和可靠性。

Objectives:Recognizing that the global navigation satellite system(GNSS)signals are seriously occluded in urban environments,it is a great challenge to achieve continuous and reliable positioning services via smartphones.Methods:An improved smartphone GNSS/micro-electro-mechanical system inertial measurement unit(MEMS IMU)tightly-coupled integration method for vehicular navigation is proposed.Specifically,the smartphone navigation system firstly conduct time updates with inertial navigation system mechanization algorithm.Then the measurement updates are realized by GNSS pseudorange,Doppler and headingangle derived by time differenced carrier phase,besides virtual constraints of vehicle motion.Re-sults:Vehicular navigation experiments using three different smartphones were carried out to evaluate the performance of the proposed algorithm.The results show that continues and reliable positioning solutions are achieved in urbanchallenging environments with horizontal and vertical accuracy of 5-6 m and 5 m in terms of root mean square,and short-term continuous navigation is also available even in tunnel scenarios where GNSS signals are totally blocked.Conclusions:The proposed algorithm is less affected by the GNSS ob-servation environment,and can improve the continuity and reliability of smartphone vehicular positioning greatly in urban complex environments.