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BLE-based floor positioning method for multi-level atrium spatial environments
Acta Geodaetica et Geophysica ( IF 1.4 ) Pub Date : 2021-06-12 , DOI: 10.1007/s40328-021-00348-2
Hongxia Qi , Yunjia Wang , Jingxue Bi , Hongji Cao , Shenglei Xu , Hui Liu

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.



中文翻译:

基于BLE的多层中庭空间环境楼层定位方法

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重点。中庭空间结构的多层建筑主要由商场和医院门诊楼组成。这种建筑分布广泛,通常人多,位置服务需求量大。室内中庭特定的空间结构使得无线信号的传播方式不同,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效果不佳。针对这种中庭结构环境,本文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。在实验中,实时动态地板定位精度达到92.7%,而5-s静态下的地板定位精度高达100%。此外,当使用回滚3s的测试数据时,也可以达到实时效果,准确率达到98.3%。该方法可单独用于实时楼层定位,适用于无线保真信号,可为气压或惯性方法提供高精度的初始楼层参考。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。数据库体积小,可推广到广泛的应用程序。此外,当使用回滚3s的测试数据时,也可以达到实时效果,准确率达到98.3%。该方法可单独用于实时楼层定位,适用于无线保真信号,可为气压或惯性方法提供高精度的初始楼层参考。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。数据库体积小,可推广到广泛的应用程序。此外,当使用回滚3s的测试数据时,也可以达到实时效果,准确率达到98.3%。该方法可单独用于实时楼层定位,适用于无线保真信号,可为气压或惯性方法提供高精度的初始楼层参考。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。数据库体积小,可推广到广泛的应用程序。它可以为气压或惯性方法提供高度准确的初始楼层参考。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。数据库体积小,可推广到广泛的应用程序。它可以为气压或惯性方法提供高度准确的初始楼层参考。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。数据库体积小,可推广到广泛的应用程序。

更新日期:2021-06-13
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