Indoor Positioning Using Wi-Fi Fingerprinting, Pedestrian Dead Reckoning and Aided INS

被引：0
|
作者：
Panyov, Alexey A. [1 ]
Golovan, Andrey A. [1 ]
Smirnov, Alexey S. [2 ]
机构：
[1] Moscow MV Lomonosov State Univ, Lab Nav & Control, Moscow, Russia
[2] Moscow MV Lomonosov State Univ, Dept Mech & Math, Moscow, Russia
来源：
2014 1ST IEEE INTERNATIONAL SYMPOSIUM ON INERTIAL SENSORS AND SYSTEMS (ISISS 2014) | 2014年
关键词：
strapdown INS; Kalman filter; indoor positioning; Wi-Fi fingerprinting; Pedestrian Dead Reckoning;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we propose a method of indoor navigation using a MEMS-based strapdown inertial navigation system (INS) aided by Wi-Fi signal strength measurements. This system does not rely on any special hardware, a modern smartphone with built-in MEMS sensors (accelerometers and gyroscopes) is sufficient for navigation. The developed INS navigation algorithm is built on the basis of the Kalman Filter solutions using the INS dead reckoning. It operates with positional data provided by Wi-Fi signal strength measurements and Pedestrian Dead Reckoning (PDR). The experimental results demonstrate the feasibility of operating this system with an accuracy of sigma = 1.5 m.
引用
收藏
页码：155 / 156
页数：2
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