Obstruction-invariant occupant localization using footstep-induced structural vibrations
Obstruction-invariant occupant localization using footstep-induced structural vibrations
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DOI：
10.1016/j.ymssp.2020.107499
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发表时间：
2021-05-15
影响因子：
8.4
通讯作者：
Noh, Hae Young
中科院分区：
文献类型：
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作者：
Mirshekari, Mostafa;Fagert, Jonathon;Noh, Hae Young
在这篇文章中，我们描述了障碍物对脚步引起的地板振动的影响，以实现障碍物不变的室内居住者定位。居住者本地化在智能建筑应用中非常重要，例如智能医疗和能源管理。维护和安装要求限制了当前传感方法(例如，基于移动、基于射频和基于压力的传感)在实际应用中的应用。为了克服这些限制，以前的工作已经利用足迹诱导的结构振动来定位乘员。这些方法背后的主要直觉是，脚步引起的地板振动波需要不同的时间才能到达不同的传感器。然后，可以利用这些到达时间差(TDOA)通过假设足迹和各种传感器位置之间的相似速度来定位足迹。这一假设使这些方法适用于开阔区域；然而，真正的建筑具有各种类型的障碍物(例如，墙、家具等)。这会影响波的传播速度，从而显著降低定位精度。因此，以前的工作需要在脚步和传感器之间畅通无阻地进行准确的乘员定位，这增加了对传感密度的要求，从而增加了仪器和维护成本。我们观察到，障碍物质量是影响波传播速度和降低定位精度的关键因素之一。因此，为了克服障碍的挑战，我们根据波路上障碍物的存在和质量，通过考虑足迹和传感器之间的不同速度来定位足迹。具体地说，我们(1)通过表征波的衰减率来检测和估计障碍物的质量，(2)使用估计的质量通过兰姆波特征对速度-质量关系进行建模来找到用于定位的传播速度，以及(3)引入非各向同性多边化方法，该方法稳健地利用这些传播速度来定位足迹(和居住者)。在现场实验中，我们获得了0.61米的平均定位误差，这(1)与无障碍物时的平均定位误差相同，(2)与基线方法相比提高了1.6倍。(C)2020作者。爱思唯尔有限公司出版。
In this paper, we characterize the effects of obstructions on footstep-induced floor vibrations to enable obstruction-invariant indoor occupant localization. Occupant localization is important in smart building applications such as smart healthcare and energy management. Maintenance and installment requirements limit the application of current sensing approaches (e.g., mobile-based, RF-based, and pressure-based sensing) in real-life applications. To overcome these limitations, prior work has utilized footstep-induced structural vibrations for occupant localization. The main intuition behind these approaches is that the footstep-induced floor vibration waves take different amounts of time to arrive at different sensors. These Time-Differences-of-Arrival (TDoA) can then be leveraged to locate the footstep by assuming similar velocities between the footstep and various sensor locations. This assumption makes these approaches suitable for open areas; however, real buildings have various types of obstructions (e.g., walls, furniture, etc.) which affect wave propagation velocities and hence significantly reduce localization accuracy. Therefore, the prior work requires unobstructed paths between footsteps and sensors for accurate occupant localization, which increases the sensing density requirement and thus, instrumentation and maintenance costs. We have observed that the obstruction mass is one of the key factors in affecting the wave propagation velocity and reducing the localization accuracy. Therefore, to overcome the obstruction challenge, we localize footsteps by considering different velocities between the footsteps and sensors depending on the existence and mass of obstruction on the wave path. Specifically, we (1) detect and estimate the mass of the obstruction by characterizing the wave attenuation rate, (2) use this estimated mass to find the propagation velocities for localization by modeling the velocity-mass relationship through the lamb wave characteristics, and (3) introduce a non-isotropic multilateration approach which robustly leverages these propagation velocities to locate the footsteps (and the occupants). In field experiments, we achieved average localization error of 0.61 meters, which is (1) the same as the average localization error when there is no obstruction and (2) 1.6X improvement compared to the baseline approach. (C) 2020 The Authors. Published by Elsevier Ltd.