School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology Chinese Academy of Sciences, Beijing 200190, China.
Sensors (Basel). 2020 May 9;20(9):2698. doi: 10.3390/s20092698.
With the widespread development of location-based services, the demand for accurate indoor positioning is getting more and more urgent. Floor positioning, as a prerequisite for indoor positioning in multi-story buildings, is particularly important. Though lots of work has been done on floor positioning, the existing studies on floor positioning in complex multi-story buildings with large hollow areas through multiple floors still cannot meet the application requirements because of low accuracy and robustness. To obtain accurate and robust floor estimation in complex multi-story buildings, we propose a novel floor positioning method, which combines the Wi-Fi based floor positioning (BWFP), the barometric pressure-based floor positioning (BPFP) with HMM and the XGBoost based user motion detection. Extensive experiments show that using our proposed method can achieve 99.2% accuracy, which outperforms other state-of-the-art floor estimation methods.
随着基于位置的服务的广泛发展，对准确的室内定位的需求变得越来越迫切。楼层定位作为多层建筑室内定位的前提，尤为重要。尽管已经有很多关于楼层定位的研究，但现有的复杂多层建筑中通过多层的大面积空洞的楼层定位研究仍然无法满足应用需求，因为其准确性和鲁棒性较低。为了在复杂的多层建筑物中获得准确和鲁棒的楼层估计，我们提出了一种新的楼层定位方法，该方法结合了基于 Wi-Fi 的楼层定位（BWFP）、基于气压的楼层定位（BPFP）、HMM 和基于 XGBoost 的用户运动检测。大量实验表明，使用我们提出的方法可以达到 99.2%的准确率，优于其他最先进的楼层估计方法。
