基于因子图优化和李群空间表征的室内行人协同导航  

Collaborative indoor pedestrian navigation based on factor graph optimization and Lie group spatial representation

作　　者：黎蕾蕾[1] 王明曦 卜继军[2] 阳洪[2] 谢长城 余平 LI Leilei;WANG Mingxi;BU Jijun;YANG Hong;XIE Changcheng;YU Ping(College of Aerospace Engineering,Chongqing University,Chongqing 400044,China;The 26th Institute of China Electronics Technology Group Corporation,Chongqing 400060,China;Chongqing Jiuzhou Starnav Systems Co.,Ltd.,Chongqing 400084,China)

机构地区：[1]重庆大学航空航天学院,重庆400044 [2]中国电子科技集团公司第二十六研究所,重庆400060 [3]重庆九洲星熠导航设备有限公司,重庆400084

出　　处：《中国惯性技术学报》2023年第5期444-451,共8页Journal of Chinese Inertial Technology

基　　金：重庆市自然科学基金面上项目(CSTB2022NSCQ-MSX1445);武汉大学测绘遥感信息工程国家重点实验室开放研究基金(20P02)。

摘　　要：在室内环境中为行人提供导航和定位服务一直具有很高的挑战性。针对无基础设施的室内环境中行人编队导航问题,提出基于因子图优化和李群空间表征的室内行人协同导航方法,采用李群中二维特殊欧式群(SE(2))空间描述行人的运动状态,利用多用户多历元PDR/UWB观测信息,通过非线性优化求解行人编队运动状态的最优估计。实验结果表明,相较于行人航位推算方法和基于EKF的协同导航方法,本文提出的协同导航方法平均定位误差分别减小了34.4%与10.4%,编队相对距离误差分别减小了76.2%与45.4%,能有效提高行人编队整体定位精度。Providing navigation and localization services for pedestrians in indoor environments has always been challenging.To address the problem of pedestrian formation navigation in indoor environments without infrastructure,a collaborative indoor pedestrian navigation based on factor graph optimization and Lie group spatial representation is proposed.The two-dimensional special Euclidean-group(SE(2))space in Lie group is used to describe the motion state of pedestrians,and multi-user and multi-calendar PDR/UWB observation information is used to optimize the optimal estimation of pedestrian formation motion state by nonlinear solution.The experimental results show that compared with the PDR and EKF algorithms,the average positioning error of the proposed algorithm is reduced by 34.4%and 10.4%,respectively,and the relative distance error of the formation is reduced by 76.2%and 45.4%,respectively,which can effectively improve the positioning accuracy of the pedestrian formation.

关 键 词：协同导航 因子图 李群 室内行人定位 

分 类 号：U666.1[交通运输工程—船舶及航道工程]