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

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

扫码查看
原文链接
  • 万方数据
  • 维普
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.

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

Qu Wang、Meixia Fu、Jianquan Wang、Lei Sun、Rong Huang、Xianda Li、Zhuqing Jiang、Yan Huang、Changhui Jiang

展开 >

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

Research Institute of China Unicom,Beijing,100190,China

School of Artificial Intelligence,Beijing University of Posts and Telecommunications,Beijing,100876,China

Department of Automation Tsinghua University,Beijing,100084,China

GEOLOC Laboratory,Université Gustave Eiffel,Paris,77454,France

展开 >

National Key Research and Development ProgramChina Postdoctoral Science FoundationGuang Dong Basic and Applied Basic Research FoundationGuangdong Key Research and Development ProgramCentral Guidance on Local Science and Technology Development Fund of Shanxi ProvinceFundamental Research Funds for Central UniversitiesInterdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)National Natural Science Foundation of China

2020YFB17088002021M7003852021A15151105772020B0101130007YDZJSX2022B019FRF-MP-20-37FRF-IDRY-21-00562002026

2024

10.1016/j.dt.2023.03.001

防务技术
中国兵工学会

防务技术

CSTPCD
影响因子：0.358
ISSN：2214-9147
年,卷(期)：2024.33(3)
  • 57