【作者】 王子璇； 赵洪博； 庄忱； 冯文全；

【Author】 Wang Zixuan;Zhao Hongbo;Zhuang Chen;Feng Wenquan;Beihang University;

【机构】 北京航空航天大学；

【摘要】 近年来,车辆GNSS定位受到越来越多的关注,然而在城市环境下,高楼的遮挡和复杂的电磁环境都影响着系统位置服务的可靠性。为了保障车辆定位的可靠性,定位系统需要实时监测定位结果并排除潜在的异常数据。随着导航卫星系统的发展,定位系统的可见卫星不断增多,故障子集扩大,故障遍历搜索的计算量也随之增加,这将对有限的车载端带来更沉重的运行负担。现有的故障顺序遍历检测方法耗时长,不满足故障检测的低时延需求。本文提出了一种基于邻车先验信息的分组遍历故障检测方法,通过对邻近车辆之间的时间、空间相关性分析,以卫星高度角、方向角为指标建立故障子集,实现对故障子集的压缩。当故障发生时,利用周边节点的故障卫星数据作为先验信息,对本地车辆故障分组遍历顺序进行优化,实现更高效率的故障检测与隔离,提高系统的故障遍历搜索效率。初步实验结果表明,在车辆编队行驶的情况下,该方案可在更短时间内检测隔离故障,从而提升车辆定位系统的可靠性。更多还原

【Abstract】 In recent years, GNSS positioning of vehicles has received more and more attention. However, in the urban environment, the shelter of tall buildings and the complex electromagnetic environment all affect the reliability of the system location service. In order to ensure the reliability of vehicle positioning, the positioning system needs to monitor the positioning results in real time and eliminate the potential abnormal data. With the development of navigation satellite system, the number of visible satellites in positioning system is increasing, the fault subset is expanding, and the computational amount of fault traversal search is also increasing, which will bring more heavy operation burden to the limited on-board terminal. The existing fault sequence traversal detection method takes a long time and cannot meet the requirement of low delay of fault detection. In this paper, a grouping traversal fault detection method based on the prior information of adjacent vehicles is proposed. By analyzing the temporal and spatial correlation between adjacent vehicles, the fault subset is established by taking the satellite altitude Angle and direction Angle as the index, and the fault subset is compressed. When a fault occurs, the fault satellite data of the surrounding nodes are used as the prior information to optimize the local vehicle fault grouping traversal sequence, achieve more efficient fault detection and isolation, and improve the system’s fault traversal search efficiency. Preliminary experimental results show that the proposed scheme can detect and isolate faults in a shorter time when vehicles are driving in formation, thus improving the reliability of the collaborative positioning system.更多还原