Smartphone Inertial Sensor-Based Indoor Localization and Tracking With iBeacon Corrections

被引:173
作者
Chen, Zhenghua [1 ]
Zhu, Qingchang [1 ]
Soh, Yeng Chai [1 ]
机构
[1] Nanyang Technol Univ, Dept Elect & Elect Engn, Nanyang Ave, Singapore 639798, Singapore
基金
新加坡国家研究基金会;
关键词
Extended Kalman filter; iBeacon; indoor localization and tracking; smartphone inertial sensors; FOOT-MOUNTED IMU; KALMAN FILTER; NAVIGATION; WIFI;
D O I
10.1109/TII.2016.2579265
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Global Positioning System (GPS) can be readily used for outdoor localization, but GPS signals are degraded in indoor environments. How to develop a robust and accurate indoor localization system is an emergent task. In this paper, we propose a smartphone inertial sensor-based indoor localization and tracking system with occasional iBeacon corrections. Some important issues in a smartphone-based pedestrian dead reckoning (PDR) approach, i. e., step detection, walking direction estimation, and initial point estimation, are studied. One problem of the PDR approach is the drift with walking distance. We apply a recent technology, iBeacon, to occasionally calibrate the drift of the PDR approach. By analyzing iBeacon measurements, we define an efficient calibration range where an extended Kalman filter is utilized. The proposed localization and tracking system can be implemented in resource-limited smartphones. To evaluate the performance of the proposed approach, real experiments under two different environments have been conducted. The experimental results demonstrated the effectiveness of the proposed approach. We also tested the localization accuracy with respect to the number of iBeacons.
引用
收藏
页码:1540 / 1549
页数:10
相关论文
共 33 条
[1]  
Alzantot M, 2012, IEEE WCNC, P3204, DOI 10.1109/WCNC.2012.6214359
[2]  
[Anonymous], 2012, P 10 INT C MOB SYST, DOI DOI 10.1145/2307636.2307655
[3]  
[Anonymous], 2006, Proceedings of the 3rd Workshop on Positioning, Navigation and Communication
[4]  
[Anonymous], 2015, ESTIMOTE BEACONS
[5]  
[Anonymous], 2015, ANDROID DEV
[6]   Simultaneous localization and mapping (SLAM): Part II [J].
Bailey, Tim ;
Durrant-Whyte, Hugh .
IEEE ROBOTICS & AUTOMATION MAGAZINE, 2006, 13 (03) :108-117
[7]   A Trainingless WiFi Fingerprint Positioning Approach Over Mobile Devices [J].
Bisio, Igor ;
Cerruti, Matteo ;
Lavagetto, Fabio ;
Marchese, Mario ;
Pastorino, Matteo ;
Randazzo, Andrea ;
Sciarrone, Andrea .
IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 2014, 13 :832-835
[8]   Locating using Prior Information: Wireless Indoor Localization Algorithm [J].
Chen, Yuanfang ;
Crespi, Noel ;
Lv, Lin ;
Li, Mingchu ;
Ortiz, Antonio M. ;
Shu, Lei .
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2013, 43 (04) :463-464
[9]   Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization [J].
Chen, Zhenghua ;
Zou, Han ;
Jiang, Hao ;
Zhu, Qingchang ;
Soh, Yeng Chai ;
Xie, Lihua .
SENSORS, 2015, 15 (01) :715-732
[10]  
Craig J.J., 2005, INTRO ROBOTICS MECH, V3