防务技术2024，Vol.33Issue(3) ：573-587.DOI:10.1016/j.dt.2023.03.001

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

Qu Wang Meixia Fu Jianquan Wang Lei Sun Rong Huang Xianda Li Zhuqing Jiang Yan Huang Changhui Jiang
防务技术2024，Vol.33Issue(3) ：573-587.DOI:10.1016/j.dt.2023.03.001
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  • 维普
  • 万方数据

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

Qu Wang 1Meixia Fu 2Jianquan Wang 2Lei Sun 2Rong Huang 3Xianda Li 3Zhuqing Jiang 4Yan Huang 5Changhui Jiang6
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作者信息

  • 1. School of Automation Science and Electrical Engineering,University of Science and Technology Beijing,Beijing,100083,China;Shunde Innovation School,University of Science and Technology Beijing,Fo Shan,528399,China
  • 2. School of Automation Science and Electrical Engineering,University of Science and Technology Beijing,Beijing,100083,China
  • 3. Research Institute of China Unicom,Beijing,100190,China
  • 4. School of Artificial Intelligence,Beijing University of Posts and Telecommunications,Beijing,100876,China
  • 5. Department of Automation Tsinghua University,Beijing,100084,China
  • 6. GEOLOC Laboratory,Université Gustave Eiffel,Paris,77454,France
  • 折叠

Abstract

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83％of the total traveled distance.

Key words

Indoor positioning/Inertial navigation system(INS)/Zero-velocity update(ZUPT)/Internet of things(IoTs)/Location-based service(LBS)

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基金项目

National Key Research and Development Program(2020YFB1708800)

China Postdoctoral Science Foundation(2021M700385)

Guang Dong Basic and Applied Basic Research Foundation(2021A1515110577)

Guangdong Key Research and Development Program(2020B0101130007)

Central Guidance on Local Science and Technology Development Fund of Shanxi Province(YDZJSX2022B019)

Fundamental Research Funds for Central Universities(FRF-MP-20-37)

Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(FRF-IDRY-21-005)

National Natural Science Foundation of China(62002026)

出版年

2024
防务技术
中国兵工学会

防务技术

CSTPCD
影响因子：0.358
ISSN：2214-9147
参考文献量57
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