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A Pedestrian Dead-Reckoning System for Walking and Marking Time Mixed Movement Using an SHSs Scheme and a Foot-Mounted IMU

机译:使用SHSs方案和脚安装式IMU的步行和记时混合运动的行人死胡同系统

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摘要

A pedestrian dead-reckoning (PDR) system based on micro-inertial technology usually uses a sensor integrated with a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer and is attached to the person's body (usually on the foot) to acquire the trajectory of the pedestrian. Although a variety of PDR system solutions have been proposed, the PDR solution for marking time and walking hybrid motions has not been formally proposed and solved. Therefore, in this paper, we propose the PDR system using a step-and-heading system scheme for marking time and walking hybrid motion. The main contributions include: 1) an adaptive gait partitioning method for walking and marking time hybrid motions is proposed; 2) a motion classification algorithm that uses a multi-layer perceptron to classify whether each step is walking or marking time is proposed; and 3) a new step length estimator based on several currently proposed models is proposed. Finally, an extended Kalman filtering algorithm combining heuristic heading reduction, flat-ground hypothesis, and cardinal heading aided inertial navigation techniques is used for heading estimation. We evaluate the effectiveness of the proposed algorithm through experiments, and the experimental results show that the average position error of the two groups of test experiments based on marking time and walking hybrid motion is 0.42% and 0.6%, respectively.
机译:基于微惯性技术的行人专用推重(PDR)系统通常使用集成了三轴陀螺仪,三轴加速度计和三轴磁力计的传感器,并固定在人体上(通常在人体脚)以获取行人的轨迹。尽管已经提出了多种PDR系统解决方案,但是尚未正式提出和解决用于标记时间和步行混合运动的PDR解决方案。因此,在本文中,我们提出了一种使用步进和前进系统方案来标记时间和步行混合运动的PDR系统。主要的贡献包括:1)提出了一种用于步行和标记时间混合运动的自适应步态划分方法; 2)提出了一种运动分类算法,该算法使用多层感知器对每个步骤是步行还是标记时间进行分类; 3)提出了一种基于几种当前提出的模型的新步长估计器。最后,将结合启发式航向减少,平地假设和主航向辅助惯性导航技术的扩展卡尔曼滤波算法用于航向估计。我们通过实验评估了该算法的有效性,实验结果表明,基于标记时间和步行混合运动的两组测试实验的平均位置误差分别为0.42%和0.6%。

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