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以全球导航卫星系统(GNSS)定位与专用短程无线通信(DSRC)协同定位的集成信息融合为目标,在DSRC协同定位层面,基于水平精度因子最小化原则,提出了一种邻车节点的优选策略。在GNSS/DSRC融合定位层面,采用分散式融合估计思想,设计了一种松耦合模式下的车辆组合定位方法,基于GNSS、DSRC并行滤波进行全局估计,利用反馈策略改善了对不同定位条件的适应能力。利用车路协同仿真平台对协同车辆定位方法进行了仿真验证。验证结果表明:邻车节点优选策略显著提升了DSRC定位精度,将其用于GNSS/DSRC融合定位,在常规运行条件下,带反馈机制的分散式估计精度优于单传感器模式与无反馈分散式估计精度;在给定的GNSS多径干扰条件下,东向、北向位置估计的均方根误差与单GNSS模式相比分别降低了42.6%和37.0%,与集中式融合估计相比分别降低了24.8%和20.3%。协同车辆定位方法的定位性能优于常规定位方案,对GNSS多径干扰条件具有良好的适应能力,具备更优的精确性、可用性及工程应用价值。
Based on the integrated information fusion of GNSS positioning and dedicated short-range wireless communication (DSRC) co-location, DSRP co-location based on the principle of minimizing the horizontal accuracy factor . In the GNSS / DSRC fusion positioning, a decentralized fusion estimation method is used to design a vehicle combination positioning method in loosely coupled mode. Global positioning is performed based on GNSS and DSRC parallel filtering, and the feedback strategy is used to improve the adaptation to different positioning conditions ability. The vehicle coordination method is used to simulate the vehicle positioning method. The verification results show that the strategy of neighbor node optimization significantly improves the positioning accuracy of DSRC and is used for GNSS / DSRC fusion positioning. Under normal operation conditions, the decentralized estimation accuracy with feedback mechanism is superior to that of single sensor mode and feedbackless decentralized Under the given GNSS multipath interference conditions, the root mean square error (RMSE) of location estimation in the east and north directions decreases by 42.6% and 37.0% respectively compared with the single GNSS model, which is lower than that in the centralized fusion estimation 24.8% and 20.3%. The positioning performance of the coordinated vehicle positioning method is superior to the conventional positioning scheme, and has good adaptability to GNSS multipath interference conditions, and has better accuracy, usability and engineering application value.