复杂环境智能手机RTK/DR车载组合定位方法

针对在手机车载定位场景下,手机RTK易受复杂环境干扰、惯导数据更新航向角易发散等问题,本文提出一种结合OSM地图数据的RTK/DR松组合定位方法.航位推算过程中,基于OSM数据,结合组合定位结果、车辆运动状态等信息,设计了点到线的几何匹配方法,使用匹配到的道路方向修正航向角.松组合阶段,使用标准Kalman滤波对位置和速度进行估计.为了减小RTK大幅漂移或跳动对松组合结果的影响,本文设置了松组合开关,结合RTK抗差Kalman解算中的协方差阵、车辆运动方向、RTK定位航向角变化量综合判断是否进行量测更新.本文采用P30、P40智能手机共进行6组实验,结果表明:OSM数据的引入能够有效控制航向角误差累积,使纯航位推算的轨迹与基准更加一致;相比于手机RTK,增加了开关的RTK/DR松组合定位性能得到提升,有效抑制了大幅跳动的误差点.

Integrated mobile phone RTK/DR vehicle positioning in complex environment

Mobile phone RTK is vulnerable to interferences from complex environment,and the heading angle of inertial navigation data is easily divergent in scenario of mobile phone vehicle positioning.To address these problems,this paper proposes an RTK/DR loose combination positioning method combined with OSM map data.In the process of dead reckoning,based on the OSM data,combined with the information of combined positioning results and vehicle motion state,a geometric matching method from point to line was designed,and the matched road direction was used to correct heading angle.In the loose combination stage,the standard Kalman filter was used to estimate the position and velocity.In order to reduce the influence of large drift or jump of RTK on the results of loose combination,a loose combination switch was set,which can comprehensively judge whether to update the measurement by combining the covariance matrix,the vehicle''s moving direction and the change of RTK positioning heading angle in RTK robust Kalman solution.Then six groups of experiment were carried out by using P30 and P40 smart phones.The results show that the introduction of OSM data can effectively solve the accumulation of heading angle error,which makes dead reckoning trajectory more consistent with the benchmark.Compared with mobile RTK,the proposed RTK/DR loose combination with switch improves positioning performance,and effectively suppresses error points of large jumps.