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HERMES: Pedestrian Real-Time Offline Positioning and Moving Trajectory Tracking System Based on MEMS Sensors

机译:HERMES:基于MEMS传感器的行人实时离线定位和移动轨迹跟踪系统

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With the development of positioning technology, sensor-based positioning has become the most commonly used positioning method because it is more low-cost and efficient with the popularity of smart phones. In this paper, we construct a pedestrian real-time offline positioning and moving trajectory tracking system (HERMES) which only relies on the sensors inside smart phones. In HERMES, based on Pedestrian Dead Reckoning (PDR) model, a stable and accurate pedestrian gait recognition is achieved through the rare double sliding window, the pedestrian step length is estimated in real time by a training pedestrian step length model, and the pedestrian real-time course angle is available through orientation sensor inside smart phones. Thus, if given a pedestrian's initial position, the system can implement the real-time offline pedestrian positioning and moving trajectory tracking. Experiments show the pedestrian gait recognition algorithm implemented in this paper has a high accuracy and the positioning effect is satisfactory. The moving trajectory tracked by the HERMES has a small deviation from the experimenter's actual trajectory.
机译:随着定位技术的发展,基于传感器的定位已经成为最常用的定位方法,因为随着智能手机的普及,基于传感器的定位更加廉价,高效。在本文中,我们构建了仅依赖智能手机内部传感器的行人实时离线定位和移动轨迹跟踪系统(HERMES)。在HERMES中,基于行人航位推算(PDR)模型,通过罕见的双滑动窗口实现了稳定,准确的行人步态识别,并通过训练行人步长模型实时估算了行人步长,而行人真实通过智能手机内的方向传感器可以获得随时间变化的航向角。因此,如果给定行人的初始位置,则该系统可以实现实时离线行人定位和移动轨迹跟踪。实验表明,本文所实现的步行步态识别算法具有较高的精度,定位效果令人满意。 HERMES跟踪的移动轨迹与实验者的实际轨迹有很小的偏差。

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