Onur Önder, G. Ghinea, Tor-Morten Grønli, T. Serif
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引用次数: 0
摘要
智能设备的普及极大地改变了人们的日常生活方式。如今,智能设备除了最初的传播者角色之外,还扮演着向导、伙伴和辅助的角色。很长一段时间以来,人们一直在使用导航系统和移动电话作为他们汽车的导航仪。事实上,人们对使用Wi-Fi、蓝牙和超宽带等技术实现类似的室内导航系统很感兴趣。然而,拟议的室内导航解决方案要么过于昂贵,无法实施和维护,要么不够精确,无法得到更广泛的接受。据此,本文提出了一种利用智能设备内置传感器的混合行人航位推算(PDR)方法。作为本研究的一部分,作者实施了三种行人航位推算方法,即PDR、Personal PDR和Hybrid p -PDR,并在现实环境中进行评估。评估结果表明,混合P-PDR方法利用用户的行走模式和低能信标信号,可以在室内环境中为用户导航,平均距离误差最小为0.77米,最大为1.35米。
Indoor Navigation Using Hybrid Personal Pedestrian Dead Reckoning (Hybrid P-PDR)
The proliferation of smart devices has dramatically changed how people live their daily lives. Today, on top of their initial communicator role, smart devices act as guides, companions, and aids. For a long time, people have been using navigation systems and mobile phones as navigators in their cars. Indeed, there have been interests in implementing similar indoor navigation systems using technologies such as Wi-Fi, Bluetooth, and ultra-wideband. However, the proposed indoor navigation solutions were either too expensive to implement and maintain, or not accurate enough for a wider acceptance. Accordingly, this paper proposes a hybrid pedestrian dead reckoning (PDR) for indoor navigation, which utilizes the built-in sensors of smart devices. As part of this study, the authors implement three approaches to pedestrian dead-reckoning namely PDR, Personal PDR, and Hybrid P-PDR-and evaluate in a real-world setting. The findings of the the evaluation shows that the Hybrid P-PDR approach, which harnesses the user’s walking pattern and signals from low-energy beacons, can navigate users in an indoor environment with a minimum of 0.77 and maximum of 1.35-meter average distance error.