基于人体运动学辅助的可穿戴式行人导航系统
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摘要
针对行人导航定位问题,研究了基于人体运动学辅助的可穿戴式行人导航系统实现的关键技术。首先基于人体运动学原理构建了零速检测模型,使用最优综合判断条件有效检测出对应的零速时刻,实时进行速度和姿态的更新修正。在检测到零速时刻时,将速度误差、位置误差作为观测量,经Kalman滤波估计惯导系统误差并进行反馈校正,抑制惯导系统的误差,提高导航定位精度。研制了集信息采集、数据传输、导航解算与监控显示于一体的可穿戴式行人导航系统,可对行人的运动状态进行实时监控。所设计的基于人体运动学辅助的可穿戴式行人导航系统,平均定位误差小于行走距离的1.1%,最大不超过1.7%,验证了本系统的可靠性和适用性。
In this paper, a wearable pedestrian navigation system based on human body kinematics is studied. The human body kinematics principle is constructed based on zero velocity detection model, using the optimal comprehensive judgment conditions, it can effectively detects the zero velocity moment, update speed and attitude correction in real time.When the zero velocity moment is detected, the velocity error and position error are as the observed quantity, the Kalman filter to estimate inertial navigation system error and feedback correction, inhibition of inertial navigation system error and improve the precision of navigation. And developed a set of information collection, data transmission, navigation and monitor display in one of the wearable pedestrian navigation system, can monitor the motion state of the pedestrians. Finally,through the verification the actual data acquisition and scenario testing, this paper based on the design of human body kinematics aided wearable pedestrian navigation system, the average positioning error is less than 1. 1% of the maximum walking distance, not more than 1.7%, to verify the reliability and applicability of the system.
In this paper, a wearable pedestrian navigation system based on human body kinematics is studied. The human body kinematics principle is constructed based on zero velocity detection model, using the optimal comprehensive judgment conditions, it can effectively detects the zero velocity moment, update speed and attitude correction in real time.When the zero velocity moment is detected, the velocity error and position error are as the observed quantity, the Kalman filter to estimate inertial navigation system error and feedback correction, inhibition of inertial navigation system error and improve the precision of navigation. And developed a set of information collection, data transmission, navigation and monitor display in one of the wearable pedestrian navigation system, can monitor the motion state of the pedestrians. Finally,through the verification the actual data acquisition and scenario testing, this paper based on the design of human body kinematics aided wearable pedestrian navigation system, the average positioning error is less than 1. 1% of the maximum walking distance, not more than 1.7%, to verify the reliability and applicability of the system.
引文
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[2]Zhao H,Wang Z,Gao Q,et al.Smooth estimation of human foot motion for zero-velocity-update-aided inertial pedestrian navigation system[J].Sensor Review,2015,35(4):803-804.
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[4]Xiong Z,Peng H,Wang J,et al.Dynamic calibration method for SINS lever-arm effect for HCVs[J].IEEE Transaction on Aerospace&Electronic Systems,2015,51(4):2760-2771.
[5]黄欣,许建新,张苗,等.基于行人运动模态辨识的室内外无缝导航航向算法研究[J].传感技术学报,2017,30(6):878-885.HUANG Xin,XU Jian-xin,ZHANG Miao,et al.Research on heading algorithm of indoor and outdoor seamless navigation based on pedestrian motion modal identification[J].Chinese Journal of Sensors and Actuators,2017,30(6):878-885.
[6]钱伟行,曾庆化,万骏炜,等.基于人体下肢运动学机理的行人导航方法[J].中国惯性技术学报,2015,23(1):24-28.QIAN Wei-xing,ZENG Qing-hua,WAN Jun-wei,et al.Pedestrian navigation method based on kinematic mecha-nism of human lower limb[J].Journal Chinese of Inertial Technology,2015,23(1):24-28.
[7]许建新,熊智,刘建业,等.基于车辆运动模型辅助的智能手机平台车载组合导航算法[J].中国惯性技术学报,2017,25(2):203-208.XU Jian-xin,XIONG Zhi,LIU Jian-ye,et al.Vehicle integrated navigation algorithm for intelligent mobile platform based on vehicle movement model[J].Journal Chinese of Inertial Technology,2017,25(2):203-208.
[8]Li Y,Wang J,Kong X.Zero velocity update with stepwise smoothing for inertial pedestrian navigation[C].International Global Navigation Satellite Systems Society,IGNSS Symposium,2013.
[9]李辰祥.基于MEMS行人惯性导航的零速度修正技术研究[D].厦门大学,2014.LI Chen-xiang.Research on zero velocity correction technique of pedestrian inertial navigation based on MEMS[D].Xiamen University,2014.
[10]张晓东.基于MEMS惯性器件的个人导航系统研究[D].北京工业大学,2015.ZHANG Xiao-dong.Research on personal navigation system based on MEMS inertial device[D].Beijing University of Technology,2015.
[11]桂彦.基于人体运动跟踪技术的步态分析系统的设计与实现[D].中南大学,2008.GUI Yan.Design and implementation of gait analysis system based on human motion tracking technology[D].Central South University,2008.