HERMES:基于MEMS传感器的行人实时离线定位与运动轨迹跟踪系统

Xinxin Liu, Xiaolong Xu
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引用次数: 3

摘要

随着定位技术的发展,随着智能手机的普及,基于传感器的定位更低成本、更高效,已成为最常用的定位方法。本文构建了一种仅依赖智能手机内部传感器的行人实时离线定位与运动轨迹跟踪系统(HERMES)。在HERMES中,基于行人航迹推算(PDR)模型,通过罕见的双滑动窗口实现稳定准确的行人步态识别,通过训练行人步长模型实时估计行人的步长,并通过智能手机内的方向传感器获得行人的实时方向角。因此,如果给定行人的初始位置,系统可以实现实时离线行人定位和运动轨迹跟踪。实验表明,本文实现的行人步态识别算法具有较高的准确率,定位效果令人满意。HERMES跟踪的运动轨迹与实验人员的实际轨迹有很小的偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HERMES: Pedestrian Real-Time Offline Positioning and Moving Trajectory Tracking System Based on MEMS Sensors
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.
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