MMLOC: multi-mode indoor localization system based on smart access points

MMLOC: multi-mode indoor localization system based on smart access points
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MMLOC:基于智能接入点的多模式室内定位系统

DOI:
10.1145/3360774.3360776
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发表时间:
2019
期刊:
Networking and Services
影响因子:
--
通讯作者:
Nahrstedt, Klara
Nahrstedt, Klara
中科院分区:
--
文献类型:
--
作者:
Yu, Tuo;Ren, Wenyu;Nahrstedt, Klara

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基于Wi-Fi指纹的室内定位是一个活跃的研究课题。然而,现有的方法没有考虑到接入点(ap)的不稳定性,这在实践中可能是不可靠的,特别是由个人用户部署的接入点。由于Wi-Fi指纹不可靠甚至错误,这种不稳定性严重影响了定位精度。理想情况下,本地化应该只使用部署良好的ap(例如,由设施团队部署)。然而,在许多地方,这些ap的数量太少,无法实现良好的定位精度。为了解决这一问题,我们利用了配备多模天线的新兴智能ap,并构建了一种名为MMLOC的新型室内定位系统,以减少所需ap的数量。其核心思想是控制AP天线的模式,以更少的AP产生更多的指纹。设计了一种基于聚类的定位策略,使移动终端能够在不需要任何同步的情况下计算出不同天线模式下的RSSI (Received Signal Strength Indicator,接收信号强度指标)。我们已经使用智能ap和商用智能手机实现了一个原型系统。实验结果表明,MMLOC可以将所需ap的数量减少50%,并达到相同甚至更好的定位精度。
Indoor localization based on Wi-Fi fingerprints has been an active research topic for years. However, existing approaches do not consider the instability of access points (APs) which may be unreliable in practice, particularly the ones deployed by individual users. This instability impacts the localization accuracy severely, due to the unreliable or even wrong Wi-Fi fingerprints. Ideally, the localization should be done using only the well-deployed APs (e.g., deployed by facility teams). However, in many places the number of these APs is too few to achieve a good localization accuracy. To solve this problem, we leverage emerging smart APs equipped with multi-mode antennas, and build a new indoor localization system called MMLOC to reduce the number of necessary APs. The key idea is controlling the modes of AP antennas to generate more fingerprints with fewer APs. A clustering based localization strategy is designed to enable a mobile terminal to figure out the RSSI (Received Signal Strength Indicator) for different antenna modes without requiring any synchronization. We have implemented a prototype system using smart APs and commercial smartphones. Experimental results demonstrate that MMLOC can reduce the number of necessary APs by 50%, and achieve the same or even better localization accuracy.
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