三维复杂运动模式航迹推算惯性导航室内定位

doi:10.3969/j.issn.0255-8297.2014.04.003

应用科学学报 ›› 2014, Vol. 32 ›› Issue (4): 349-350.doi: 10.3969/j.issn.0255-8297.2014.04.003

三维复杂运动模式航迹推算惯性导航室内定位

陈兴秀1，张金艺1,2,3，晏理1，刘江2，周文强2

1. 上海大学特种光纤与光接入网省部共建教育部重点实验室，上海200072
2. 上海大学微电子研究与开发中心，上海200072
3. 上海大学教育部新型显示与系统应用重点实验室，上海200072

收稿日期:2014-05-12 修回日期:2014-05-19 出版日期:2014-07-31 发布日期:2014-05-19
作者简介:张金艺，研究员，通信类SoC 设计与无线传感器网络，E-mail: zhangjinyi@staff.shu.edu.cn
基金资助:
国家“863”高技术研究发展计划基金(No.2013AA03A1121, No.2013AA03A1122)；上海市教委重点学科项目基金(No.J50104)
资助

Inertial Indoor Navigation with 3D Complex Motion Mode of Pedestrian Dead Reckoning

CHEN Xing-xiu1, ZHANG Jin-yi1,2,3, YAN Li1, LIU Jiang2, ZHOU Wen-qiang2

1. Key Laboratory of Special Fiber Optics and Optical Access Networks,
Ministry of Education, Shanghai 200072, China
2. Microelectronic Research and Development Center, Shanghai 200072, China
3. Key Laboratory of Advanced Displays and System Application, Ministry of Education,
Shanghai University, Shanghai 200072, China

Received:2014-05-12 Revised:2014-05-19 Online:2014-07-31 Published:2014-05-19

摘要/Abstract

摘要： 在微机电惯性测量单元(micro-electro-mechanical system-inertial measurement unit, MEMS-IMU)人体室内定位技术研究领域中，行人航迹推算法(pedestrian dead reckoning, PDR)具有计算简便、对传感器精度要求低的优点，得到了较为广泛的应用，但传统的PDR 研究通常只针对单一的二维前进行走运动模式，这与人体实际的三维复杂运动模式相距甚远. 该文从人体三维室内定位研究角度出发，通过10 轴MEMS 传感器采集人体运动原始信息，提出了三维复杂运动模式航迹推算法. 首先使用双零点交叉区间内的峰值双轴检测法与俯仰角检测法来检测5 类非行走运动模式，排除其对有效跨步检测的干扰；其次使用相位反转法与气压值突变法区分3 类行走运动模式，提取出不同类型的有效跨步；最后针对每一个有效跨步求解出人体位置的三维坐标值，完成人体三维室内定位. 实验表明，所提出的三维复杂运动模式航迹推算法在人体实际室内运动中，相较传统的峰值检测和零点交叉法PDR，水平定位精度提升了99%，并且高度定位精度可以达到92.4%.

关键词: 三维, 室内定位, 行人航迹推算, 微机电系统

Abstract: In human indoor navigation research, pedestrian dead reckoning (PDR) involves less calculation with lower accuracy sensor, and therefore becomes popular in micro-electro-mechanical system-inertial measurement unit (MEMS-IMU). However, conventional PDR approaches only consider 2D forward motion mode,which is unrealistic. This paper uses an approach named 3D complex motion mode PDR to describe human’s indoor life. By collecting the original human motion information with a 10-axis MEMS sensor, this paper proposes a 3D complex motion mode PDR algorithm. 2-axis detection of 2-peak within double zero-crossing and pitch detection methods are used to detect 5 kinds of non-walking motion mode to reduce interference of step detection. Phase reversal and pressure mutation methods are used to distinguish 3 kinds of walking motion mode to record every effective step. The 3D coordinates of the human location are then calculated. Experimental results show that, for the actual human indoor 3D and complex motion mode, the proposed algorithm increases the horizontal positioning accuracy by 99% compared with conventional peak detection and zero-crossing detection PDR. Accuracy of height positioning reaches 92.4%.

Key words: 3D, indoor navigation, pedestrian dead reckoning (PDR), micro-electro-mechanical system (MEMS)

中图分类号:

TP273

陈兴秀1，张金艺1,2,3，晏理1，刘江2，周文强2. 三维复杂运动模式航迹推算惯性导航室内定位[J]. 应用科学学报, 2014, 32(4): 349-350.

CHEN Xing-xiu1, ZHANG Jin-yi1,2,3, YAN Li1, LIU Jiang2, ZHOU Wen-qiang2. Inertial Indoor Navigation with 3D Complex Motion Mode of Pedestrian Dead Reckoning[J]. Journal of Applied Sciences, 2014, 32(4): 349-350.

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三维复杂运动模式航迹推算惯性导航室内定位

Inertial Indoor Navigation with 3D Complex Motion Mode of Pedestrian Dead Reckoning

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