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基于零速修正与姿态自观测的惯性行人导航算法

戴洪德 张笑宇 郑百东 戴邵武 郑伟伟

戴洪德, 张笑宇, 郑百东, 等 . 基于零速修正与姿态自观测的惯性行人导航算法[J]. 北京航空航天大学学报, 2022, 48(7): 1135-1144. doi: 10.13700/j.bh.1001-5965.2021.0037
引用本文: 戴洪德, 张笑宇, 郑百东, 等 . 基于零速修正与姿态自观测的惯性行人导航算法[J]. 北京航空航天大学学报, 2022, 48(7): 1135-1144. doi: 10.13700/j.bh.1001-5965.2021.0037
DAI Hongde, ZHANG Xiaoyu, ZHENG Baidong, et al. Inertial pedestrian navigation algorithm based on zero velocity update and attitude self-observation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1135-1144. doi: 10.13700/j.bh.1001-5965.2021.0037(in Chinese)
Citation: DAI Hongde, ZHANG Xiaoyu, ZHENG Baidong, et al. Inertial pedestrian navigation algorithm based on zero velocity update and attitude self-observation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1135-1144. doi: 10.13700/j.bh.1001-5965.2021.0037(in Chinese)

基于零速修正与姿态自观测的惯性行人导航算法

doi: 10.13700/j.bh.1001-5965.2021.0037
基金项目: 

国防科技项目基金 F062102009

山东省自然科学基金 ZR2017MF036

山东省高等学校青年创新团队项目 2020KJN003

详细信息
    通讯作者:

    戴洪德, E-mail: 13954559561@126.com

  • 中图分类号: V241.62

Inertial pedestrian navigation algorithm based on zero velocity update and attitude self-observation

Funds: 

Defense Science and Technology Project Foundation of China F062102009

Shandong Provincial Natural Science Foundation ZR2017MF036

Young Innovation Team of Colleges and Universities in Shandong Province 2020KJN003

More Information
  • 摘要:

    针对惯性行人导航中航向角发散致使导航精度降低的问题,提出了一种基于零速修正与姿态自观测的惯性行人导航算法。通过四条件零速检测算法对行走步态中的零速区间进行检测。在检测得到的零速区间内,利用零速修正算法原理构造速度误差的观测量;利用零速区间内行人脚部与地面保持静止、只受到重力加速度及姿态角不变的特性,构造姿态角误差的观测量。应用卡尔曼滤波对零速区间内的姿态角、速度及位置的误差进行估计。利用得到的误差状态估计结果对行人导航进行误差校正,提高惯性行人导航的精度。实验表明:小范围矩形路径中,所提算法的导航轨迹相对误差平均值仅占总路程的0.98%,比零速修正算法减小了78.11%;导航轨迹误差标准差仅为0.14 m,比零速修正算法减小了88.62%;400 m标准操场闭合路径中解算终点相对位置误差仅为1.18%。解算轨迹与实际轨迹匹配度较高,具有良好的应用价值。

     

  • 图 1  行人步态周期示意图

    Figure 1.  Schematic diagram of pedestrian foot gait cycle

    图 2  传感器安装实物图及惯性行人导航系统构成

    Figure 2.  Physical map of sensor installation positions and composition of inertial pedestrian navigation system

    图 3  基于零速修正与姿态自观测的惯性行人导航算法原理

    Figure 3.  Working principle of zero velocity update and attitude self-observation algorithm of inertial pedestrian navigation

    图 4  四条件零速检测算法零速检测结果

    Figure 4.  Results of zero velocity test of four-condition zero velocity detection algorithm

    图 5  纯惯导算法轨迹

    Figure 5.  Trajectory of pure inertial navigation algorithm

    图 6  不同算法轨迹对比

    Figure 6.  Comparison of different algorithm trajectories

    图 7  实际行走轨迹参考点示意图

    Figure 7.  Schematic diagram of actual walking track reference point

    图 8  操场卫星图

    Figure 8.  Satellite image of playground

    图 9  操场行走轨迹

    Figure 9.  Trajectory of walking on playground

    表  1  三种算法位置误差与导航轨迹误差

    Table  1.   Position error and navigation track error of three kinds of algorithm m

    算法 参考点坐标 对应点坐标 Δγ ΔR ΔS
    零速修正算法(算法1) (0, 9) (0.68, 8.86) 0.69 2.33 1.23
    (-17, 9) (-16.63, 10.71) 1.75
    (-17, 0) (-18.52, 3.69) 3.99
    (0, 0) (-2.12, -1.93) 2.87
    零速修正与俯仰角、滚转角观测算法(算法2) (0, 9) (0.62, 8.83) 0.64 0.86 0.41
    (-17, 9) (-16.84, 10.00) 1.01
    (-17, 0) (-17.64, 1.29) 1.44
    (0, 0) (0.04, -0.35) 0.35
    零速修正与姿态自观测算法(算法3) (0, 9) (0.50, 8.84) 0.52 0.51 0.14
    (-17, 9) (-17.00, 9.39) 0.39
    (-17, 0) (-17.36, 0.65) 0.74
    (0, 0) (0.38, 0.09) 0.39
    下载: 导出CSV

    表  2  三种算法解算终点的相对位置误差

    Table  2.   Relative position error of the end point of three kinds of algorithm

    算法 起点坐标/m 终点坐标/m 位置误差/m 相对位置误差/%
    零速修正算法(算法1) (0, 0) (-16.80, 51.33) 54.00 13.50
    零速修正与俯仰角、滚转角观测算法(算法2) (0, 0) (31.50, -0.86) 31.51 7.88
    零速修正与姿态自观测算法(算法3) (0, 0) (-1.50, 4.48) 4.72 1.18
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-01-21
  • 录用日期:  2021-07-01
  • 刊出日期:  2021-07-07

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