Research on HAR-Based Floor Positioning
Research on HAR-Based Floor Positioning
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DOI：
10.3390/ijgi10070437
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
Hongxia Qi;Yunjia Wang;Jingxue Bi;Hongji Cao;Shenglei Xu
中科院分区：
文献类型：
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作者：
Hongxia Qi;Yunjia Wang;Jingxue Bi;Hongji Cao;Shenglei Xu
地板定位是室内定位技术的一个重要方面，它与基于位置的服务（lbs）密切相关。目前，地板定位技术主要基于无线电信号和气压。前者受多径效应的影响，依赖于基础设施的支持，受不同空间结构的限制；对于后者，气压随温度和湿度变化，参考站的部署成本较高，并且需要提前校准不同的终端模型。针对这些问题，本文提出了一种新的基于人类活动识别（HAR）的地板定位方法，利用智能手机内置的传感器数据对行人活动进行分类。我们根据每一步的活动类别得到楼层变化的程度，并通过条件和阈值分析确定行人是否完成楼层切换。然后，将前一层或高精度初始层与楼层变化度相结合，计算出行人的实时楼层位置。实验场地选择了一座多层办公楼，并通过多种类型活动交替进行的过程进行验证。结果表明，该方法对行人地板位置变化的识别和定位准确率高达100%，具有良好的鲁棒性和通用性。它比基于无线信号的方法更稳定。与现有的一种基于har和气压的方法相比，本文方法允许行人在上下楼梯的过程中进行长期静态或往返活动。此外，该方法对行人动作的误判具有良好的容错性。
Floor positioning is an important aspect of indoor positioning technology, which is closely related to location-based services (LBSs). Currently, floor positioning technologies are mainly based on radio signals and barometric pressure. The former are impacted by the multipath effect, rely on infrastructure support, and are limited by different spatial structures. For the latter, the air pressure changes with the temperature and humidity, the deployment cost of the reference station is high, and different terminal models need to be calibrated in advance. In view of these issues, here, we propose a novel floor positioning method based on human activity recognition (HAR), using smartphone built-in sensor data to classify pedestrian activities. We obtain the degree of the floor change according to the activity category of every step and determine whether the pedestrian completes floor switching through condition and threshold analysis. Then, we combine the previous floor or the high-precision initial floor with the floor change degree to calculate the pedestrians’ real-time floor position. A multi-floor office building was chosen as the experimental site and verified through the process of alternating multiple types of activities. The results show that the pedestrian floor position change recognition and location accuracy of this method were as high as 100%, and that this method has good robustness and high universality. It is more stable than methods based on wireless signals. Compared with one existing HAR-based method and air pressure, the method in this paper allows pedestrians to undertake long-term static or round-trip activities during the process of going up and down the stairs. In addition, the proposed method has good fault tolerance for the misjudgment of pedestrian actions.