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一种多传感器融合的行人多模式自主定位方法 被引量:1

A Multi-mode Autonomous Positioning Method for Pedestrians Based on Multi-sensor Fusion
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摘要 在全球卫星导航系统拒止的环境里,导航信息难以获取,基于红外、超声波、射频、Wi-Fi、超宽带(UWB)等室内定位方法均需要辅助电子标签,传统航位推算法只适合前向步态的路径跟踪,在后向、左向、右向步态模式下会出现反向或垂直的路径错误。针对以上问题,该文借助移动终端的惯性测量单元数据,在不依赖任何电子标签模式导航的情况下,实现短时多模式步态行人跟踪。结果表明,通过多次重复测试,步态检测准确率≥92%,以实际车库场景为实验背景,该文方法可获得全步态模式下自主路径跟踪,路径追踪误差小于3 m。 It is difficult to obtain the navigation information in the case of GNSS rejection,while the methods based on infrared,ultrasonic,radio,Wi-Fi,ultra-wide-band need the assist of electronic label,and the traditional dead reckoning algorithm is to draw the trajectory of a pedestrian on the condition of walking forward.It may be opposite or perpendicular to the actual trajectory if the pedestrian takes backward and lateral walking.To solve the above-mentioned problems,the inertial measurement unit embedded in mobile terminal is used to realize the short-time multi-mode pedestrian tracking based on multi-sensor without relying on any electronic label.The results of repeated tests show that the detected accuracy of walking mode is higher than or equal to 92%.Taking the actual garage scene as the experimental background,this method can obtain autonomous path tracking in full walking mode,and the path tracking error is less than 3 m.
作者 亓林 刘宇 芶志平 杨勇 路永乐 邹新海 QI Lin;LIU Yu;GOU Zhiping;YANG Yong;LU Yongle;ZOU Xinhai(Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem,Chongqing University of Post and Telecommunications, Chongqing 400065,China;The 26th Research institute of China Electronic Technology Group Corporation,Chongqing 400060,China)
出处 《压电与声光》 CAS 北大核心 2020年第4期568-572,共5页 Piezoelectrics & Acoustooptics
基金 国家重点研发计划基金资助项目(2018YFF01010202,2018YFF01010201) 国家自然科学基金资助项目(61901069,61705027,11704053,51902037) 省部级人才计划基金资助项目(CSTC-CXLJRC201711) 重庆市科学技术委员会基础研究基金资助项目(CSTC-2018jcyjax0619) 重庆市教委基础研究基金资助项目(KJZH17115,KJQN201800626,KJQN201900615)。
关键词 航位推算 惯性测量单元 多模式步态 自主定位 多传感器融合 dead reckoning IMU multi-mode of walking autonomous positioning multi-sensor fusion
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