[1]王云涛,钱伟行,徐 昊,等.自适应零速修正辅助的微惯性定位系统研究[J].南京师范大学学报(工程技术版),2017,17(04):014.[doi:10.3969/j.issn.1672-1292.2017.04.003]
　Wang Yuntao,Qian Weixing,Xu Hao,et al.Research on Micro Inertial Positioning SystemBased on Adaptive Zero Velocity Updating[J].Journal of Nanjing Normal University(Engineering and Technology),2017,17(04):014.[doi:10.3969/j.issn.1672-1292.2017.04.003]
点击复制

自适应零速修正辅助的微惯性定位系统研究
分享到：

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
17卷
期数:
2017年04期
页码:
014
栏目:
电气与电子工程
出版日期:
2017-12-30

文章信息/Info

Title:
Research on Micro Inertial Positioning SystemBased on Adaptive Zero Velocity Updating
文章编号:
1672-1292(2017)04-0014-06
作者:
王云涛; 钱伟行; 徐 昊; 郑婷婷; 宋天威
南京师范大学电气与自动化工程学院,江苏 南京 210042
Author(s):
Wang Yuntao; Qian Weixing; Xu Hao; Zheng Tingting; Song Tianwei
School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210042,China
关键词:
微惯性器件; 零速修正; 步态分析; Kalman滤波器
Keywords:
MIMU; zero velocity updating; gait phase detection; Kalman filter
分类号:
U666.1
DOI:
10.3969/j.issn.1672-1292.2017.04.003
文献标志码:
A
摘要:
针对GNSS失效情况下微惯性器件漂移大引起的定位精度低的问题,研究了一种多条件辨识零速时刻,基于速度信息构建观测方程的零速修正算法,以提高微惯性系统的定位精度. 论文阐述了行人步态特性,在分析行人步态的基础上设计了基于加速度量测方差、加速度量测幅值和角速度量测能量的多条件零速检测方法,并针对室内外不同环境设置了自适应阈值. 在此基础上,构建了速度信息为系统观测值的Kalman滤波器,在零速对姿态、速度及位置误差进行估计并修正. 实验结果表明,基于上述自适应定位修正算法可有效增强零速检测的可靠性,抑制定位误差的累积,定位的精度是行进距离的1.32%.
Abstract:
Aiming at the problem that drifts error of micro inertial sensors under the condition of GNSS failure,a zero velocity updating algorithm is proposed to construct a filter model based on velocity information for observation,so as to improve the positioning accuracy. The paper describes the pedestrian gait characteristics. Based on the analysis of pedestrian gait,a zero-velocity detection algorithm with multi-condition constraints is designed by using the acceleration measurement variance,acceleration measurement amplitude and angular velocity measurement energy as measurements,and the adaptive threshold is set for different indoor and outdoor environment. On this basis,a Kalman filter with velocity information is established to estimate and correct the attitude,velocity and position error at zero speed. The experimental results show that the localization correction algorithm can effectively enhance the reliability of zero velocity detection and suppress the accumulation of positioning error,and that the accuracy of the positioning is 1.32% of the travel distance.

参考文献/References:

[1] 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 W X,ZENG Q H,WAN J W,et al. Pedestrian navigation method based on kinematic mechanism of human lower limb[J]. Journal of Chinese inertial technology,2015,23(1):24-28.(in Chinese)
[2]孙璧文,樊启高,武亚恒,等. 基于PDR/UWB紧耦合的足绑式行人导航技术[J]. 传感器与微系统,2017,36(3):43-48.
SUN B W,FAN Q G,WU Y H,et al. Foot-mounted pedestrian navigation technology based on tightly coupled PDR/UWB[J]. Transducer and microsystem technologies,2017,36(3):43-50.(in Chinese)
[3]LIU Y,LI S L,MU C,et al. Step length estimation based on D-ZUPT for pedestrian dead-reckoning system[J]. Electronics letters,2016,52(11):923-924.
[4]JOHN-OLOF N,ISAAC S,PETER H,et al. Foot-mounted INS for everybody—an open-source embedded implementation[C]//Position,Location and Navigation Symposium(PLANS). Myrtle Beach,SC,USA:IEEE/ION,2012.
[5]BIRD J,ARDEN D. Indoor navigation with foot-mounted strapdown inertial navigation and magnetic sensors[J]. IEEE wireless communications,2011,18(2):28-35.
[6]张新喜,张嵘,郭美凤,等. 足绑式行人导航偏航角误差自观测算法[J]. 中国惯性技术学报,2015,23(4):457-466.
ZHANG X X,ZHANG R,GUO M F,et al. Yaw error self-observation algorithm for pedestrian navigation via foot-mounted inertial navigation system[J]. Journal of Chinese inertial technology,2015,23(4):457-466.(in Chinese)
[7]FELIPE O S,ELDER M H,WALDEMAR C L F. Error analysis of analytical coarse alignment formulations for stationary SINS[J]. IEEE transactions on aerospace and electronic systems,2016,52(4):1 777-1 796.
[8]ABDELMOUMEN N,ZAKARIA K,JORG B,et al. Step detection for ZUPT-aided inertial pedestrian navigation system using foot-mounted permanent magnet[J]. IEEE sensors journal,2016,16(17):6 766-6 773.
[9]GHAZALEH P,NASSER M,ARNE L,et al. Continuous hidden markov model for pedestrian activity classification and gait analysis[J]. IEEE transactions on instrumentation and measurement,2013,62(5):1 073-1 083.
[10]张晓东. 基于MEMS惯性器件的个人导航系统研究[D]. 北京:北京工业大学,2015.
ZHANG X D. Study on personal navigation system based on MEMS inertial devices[D]. Beijing:Beijing University of Technology,2015.(in Chinese)
[11]田晓春,陈家斌,韩勇强,等. 多条件约束的行人导航零速区间检测算法[J]. 中国惯性技术学报,2016,24(1):1-5.
TIAN X C,CHEN J B,HAN Y Q,et al. Zero-velocity interval detection algorithm with multi-condition constraint for pedestrian navigation[J]. Journal of Chinese inertial technology,2016,24(1):1-5.(in Chinese)
[12]YUAN Z,NASER E S. Tightly-coupled integration of WiFi and MEMS sensors on handheld devices for indoor pedestrian navigation[J]. IEEE sensors journal,2016,16(1):224-234.

相似文献/References:

[1]袁 珊,万 游,孟佳杰,等.一种基于VINS/FINS组合导航方法[J].南京师范大学学报(工程技术版),2021,21(03):042.[doi:10.3969/j.issn.1672-1292.2021.03.006]
　Yuan Shan,Wan You,Meng Jiajie,et al.An Integrated Navigation Method Based on VINS/FINS[J].Journal of Nanjing Normal University(Engineering and Technology),2021,21(04):042.[doi:10.3969/j.issn.1672-1292.2021.03.006]

备注/Memo

备注/Memo:
收稿日期:2017-05-24.
基金项目:国家自然科学基金(61304227、61273057、61601228)、江苏省自然科学基金(BK20141453).
通讯联系人:钱伟行,副教授,硕士生导师,研究方向:惯性与组合导航技术. E-mail:61192@ njnu.edu.cn
更新日期/Last Update: 2017-12-30