BLE-based floor positioning method for multi-level atrium spatial environments
BLE-based floor positioning method for multi-level atrium spatial environments
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DOI：
10.1007/s40328-021-00348-2
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发表时间：
2021-06-12
影响因子：
1.4
通讯作者：
Liu H
中科院分区：
文献类型：
--
作者：
Qi H;Wang Y;Bi J;Cao H;Xu S;Liu H
如今，世界各地的城镇高楼林立，楼层定位技术逐渐成为室内定位研究的焦点。中庭空间结构的多层建筑主要包括商场和医院门诊楼。这类建筑分布广泛，通常人很多，对位置服务的需求也很高。室内中庭的特定空间结构使得无线信号的传播方式存在差异，这就导致大多数基于无线信号的楼层定位方法在这样的环境下不能很好地工作。针对这种中庭结构环境，提出了一种基于蓝牙低功耗信号的高精度多方法自适应加权融合算法。实验中，实时动态楼层定位准确率达到92.7%，而5 s静态状态下楼层定位准确率高达100%。此外，当使用3s的测试数据回滚时，也能达到实时效果，准确率达到98.3%。该方法可以单独用于实时楼层定位，它适用于无线保真信号，并且它可以为气压或惯性方法提供高度精确的初始楼层参考。它还可以与其他方法集成，以长时间提供高度准确的楼层位置。该方法采集指纹库省时省力。数据库容量小，可推广到广泛的应用程序。
Nowadays, cities and towns all over the world are dotted with high-rise buildings, and floor positioning technology has gradually become the focus of indoor positioning research. Multi-level buildings with an atrium space structure mainly consist of shopping malls and hospital outpatient buildings. This kind of building is widely spread, and they usually have a lot of people and a high demand for location-based services. The specific spatial structure of the indoor atrium makes the propagation of wireless signals different, which leads to most of the wireless signal-based floor positioning methods not working well in such an environment. Aiming at this atrium structure environment, this paper proposes a high-precision multi-method adaptive weighted fusion algorithm based on Bluetooth Low Energy signals. In experiments, the real-time dynamic floor positioning accuracy reached 92.7%, while the floor positioning accuracy in the 5-s static state was as high as 100%. Besides, when using 3 s of test data rolled back, real-time effects could also be achieved, with an accuracy of 98.3%. This method can be used alone for real-time floor positioning, it is suitable for wireless fidelity signals, and it can provide a highly accurate initial floor reference for barometric or inertial methods. It could also be integrated with other methods to provide highly accurate floor locations for long periods of time. The fingerprint library acquisition in this method saves time and effort. The database volume is small and generalizable to a wide range of applications.
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影响因子：
3.9
作者：
Ashraf, Imran;Hur, Soojung;Park, Yongwan
通讯作者：
Park, Yongwan
考虑用户方位的自适应加权K近邻指纹室内定位新方法
DOI：
10.1177/1550147718785885
发表时间：
2018-06-28
影响因子：
2.3
作者：
Bi, Jingxue;Wang, Yunjia;Wang, Yongkang
通讯作者：
Wang, Yongkang
DOI：
10.1145/3380979
发表时间：
2020-03-01
期刊：
PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT
影响因子：
--
作者：
Elbakly, Rizanne;Youssef, Moustafa
通讯作者：
Youssef, Moustafa
使用 MAC 和 RSSI 指纹向量进行多层建筑的室内定位
影响因子：
3.9
作者：
Han, Litao;Jiang, Li;Song, Shiming
通讯作者：
Song, Shiming
DOI：
10.1109/embc.2013.6610606
发表时间：
2013
期刊：
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子：
--
作者：
Bai Y;Jia W;Zhang H;Mao ZH;Sun M
通讯作者：
Sun M