A Profile-Matching Method for Wireless Positioning

This letter presents a profile-based wireless fingerprinting method, which mitigates positioning ambiguity by introducing short-term historical trajectories from dead-reckoning. This approach extends the fingerprint from one dimension to multiple, and thus enriches its diversity. Meanwhile, the multi-dimensional dynamic time warping method is introduced for matching multi-dimensional fingerprints with inaccurate profile lengths. Compared with the traditional single-point matching method, the profile-matching method provides a more reliable solution especially in environments with sparse distributed access points and a more accurate initial position. Indoor walking tests with two smartphones, in two buildings, and under four motion conditions illustrated that the proposed profile-matching method reduced the position errors by 11.5-21.6 %.

[1]  M. Reinders,et al.  Multi-Dimensional Dynamic Time Warping for Gesture Recognition , 2007 .

[2]  Xiaoji Niu,et al.  A Hybrid WiFi/Magnetic Matching/PDR Approach for Indoor Navigation With Smartphone Sensors , 2016, IEEE Communications Letters.

[3]  Chuan Heng Foh,et al.  A practical path loss model for indoor WiFi positioning enhancement , 2007, 2007 6th International Conference on Information, Communications & Signal Processing.

[4]  Alan Dodson,et al.  Impact of GPS satellite and pseudolite geometry on structural deformation monitoring: analytical and empirical studies , 2004 .

[5]  Hojung Cha,et al.  Localizing WiFi Access Points Using Signal Strength , 2011, IEEE Communications Letters.

[6]  Fengshou Gu,et al.  Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal , 2012 .

[7]  Jianxin Wu,et al.  GROPING: Geomagnetism and cROwdsensing Powered Indoor NaviGation , 2015, IEEE Transactions on Mobile Computing.

[8]  Gi-Wan Yoon,et al.  Radio Map Update Automation for WiFi Positioning Systems , 2013, IEEE Communications Letters.

[9]  Panos K. Chrysanthis,et al.  On indoor position location with wireless LANs , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[10]  Simon Schmitt,et al.  The effects of human body shadowing in RF-based indoor localization , 2014, 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[11]  Demetrios Zeinalipour-Yazti,et al.  Crowdsourced indoor localization for diverse devices through radiomap fusion , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[12]  Ian F. Akyildiz,et al.  Signal propagation techniques for wireless underground communication networks , 2009, Phys. Commun..

[13]  Naser El-Sheimy,et al.  Evaluation of Two WiFi Positioning Systems Based on Autonomous Crowdsourcing of Handheld Devices for Indoor Navigation , 2016, IEEE Transactions on Mobile Computing.

[14]  Peng Zhang,et al.  WiFi-Aided Magnetic Matching for Indoor Navigation with Consumer Portable Devices , 2015, Micromachines.

[15]  Xiaoji Niu,et al.  Autonomous Calibration of MEMS Gyros in Consumer Portable Devices , 2015, IEEE Sensors Journal.

[16]  Shih-Hau Fang,et al.  Accurate Indoor Location Estimation by Incorporating the Importance of Access Points in Wireless Local Area Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.