Locating Smartphones Indoors Using Built-In Sensors and Wi-Fi Ranging With an Enhanced Particle Filter

被引:65
|
作者
Xu, Shihao [1 ]
Chen, Ruizhi [1 ,2 ]
Yu, Yue [1 ]
Guo, Guangyi [1 ]
Huang, Lixiong [1 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
[2] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Hubei, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Wi-Fi FTM; pedestrian dead reckoning; particle filter; multi-sensors; indoor localization; TRACKING; DESIGN; PDR;
D O I
10.1109/ACCESS.2019.2927387
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sensors-based and radio frequency (RF)-based indoor localization technology is one of the keys in location-based services. The IEEE 802.11-2016 introduced the Wi-Fi fine timing measurement (FTM) protocol, which provides a new approach for Wi-Fi-based indoor localization. However, Wi-Fi signals are susceptible to complex indoor environments. To improve the positioning accuracy and stability, an enhanced particle filter (PF) with two different state update strategies, a new criterion for divergence monitoring and rapid re-initialization is proposed to integrate the advantages of pedestrian dead reckoning (PDR) and Wi-Fi FTM. In addition, an adaptive tilt compensation is proposed to improve real-time heading estimation of conventional PDR, and the Wi-Fi FTM outliers are detected by displacement estimation of the PDR. The experimental results show that the proposed PF has better localization performance than the single source positioning methods in a typical indoor scenario. The accuracy of final localization is within 1 m in 86.7% of the dynamic cases and the average calculation time is less than 0.5 s when the number of particles is 2000.
引用
收藏
页码:95140 / 95153
页数:14
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