Liu Tao, Zhang Xing, Li Qingquan, Fang Zhixiang
Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China.
Key Laboratory for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and Geoinformation, Shenzhen University, Shenzhen 518060, China.
Sensors (Basel). 2017 Aug 4;17(8):1790. doi: 10.3390/s17081790.
Localization of users in indoor spaces is a common issue in many applications. Among various technologies, a Wi-Fi fingerprinting based localization solution has attracted much attention, since it can be easily deployed using the existing off-the-shelf mobile devices and wireless networks. However, the collection of the Wi-Fi radio map is quite labor-intensive, which limits its potential for large-scale application. In this paper, a visual-based approach is proposed for the construction of a radio map in anonymous indoor environments. This approach collects multi-sensor data, e.g., Wi-Fi signals, video frames, inertial readings, when people are walking in indoor environments with smartphones in their hands. Then, it spatially recovers the trajectories of people by using both visual and inertial information. Finally, it estimates the location of fingerprints from the trajectories and constructs a Wi-Fi radio map. Experiment results show that the average location error of the fingerprints is about 0.53 m. A weighted k-nearest neighbor method is also used to evaluate the constructed radio map. The average localization error is about 3.2 m, indicating that the quality of the constructed radio map is at the same level as those constructed by site surveying. However, this approach can greatly reduce the human labor cost, which increases the potential for applying it to large indoor environments.
在许多应用中，室内空间用户定位是一个常见问题。在各种技术中，基于Wi-Fi指纹的定位解决方案备受关注，因为它可以利用现有的现成移动设备和无线网络轻松部署。然而，Wi-Fi无线电地图的收集工作相当耗费人力，这限制了其大规模应用的潜力。本文提出了一种基于视觉的方法，用于在匿名室内环境中构建无线电地图。该方法在人们手持智能手机在室内环境中行走时收集多传感器数据，例如Wi-Fi信号、视频帧、惯性读数。然后，利用视觉和惯性信息在空间上恢复人员的轨迹。最后，根据轨迹估计指纹位置并构建Wi-Fi无线电地图。实验结果表明，指纹的平均定位误差约为0.53米。还使用加权k近邻方法评估构建的无线电地图。平均定位误差约为3.2米，表明构建的无线电地图质量与实地勘测构建的地图处于同一水平。然而，这种方法可以大大降低人力成本，增加了将其应用于大型室内环境的潜力。
