WiFi-based indoor positioning

Recently, several indoor localization solutions based on WiFi, Bluetooth, and UWB have been proposed. Due to the limitation and complexity of the indoor environment, the solution to achieve a low-cost and accurate positioning system remains open. This article presents a WiFibased positioning technique that can improve the localization performance from the bottleneck in ToA/AoA. Unlike the traditional approaches, our proposed mechanism relaxes the need for wide signal bandwidth and large numbers of antennas by utilizing the transmission of multiple predefined messages while maintaining high-accuracy performance. The overall system structure is demonstrated by showing localization performance with respect to different numbers of messages used in 20/40 MHz bandwidth WiFi APs. Simulation results show that our WiFi-based positioning approach can achieve 1 m accuracy without any hardware change in commercial WiFi products, which is much better than the conventional solutions from both academia and industry concerning the trade-off of cost and system complexity.

[1]  Moe Z. Win,et al.  Fundamental Limits of Wideband Localization— Part II: Cooperative Networks , 2010, IEEE Transactions on Information Theory.

[2]  Moe Z. Win,et al.  Ranging With Ultrawide Bandwidth Signals in Multipath Environments , 2009, Proceedings of the IEEE.

[3]  Moe Z. Win,et al.  Fundamental Limits of Wideband Localization— Part I: A General Framework , 2010, IEEE Transactions on Information Theory.

[4]  Andreas Richter,et al.  Angle-based indoor positioning system for open indoor environments , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[5]  Paul Congdon,et al.  Avoiding multipath to revive inbuilding WiFi localization , 2013, MobiSys '13.

[6]  Constantinos B. Papadias,et al.  Joint angle and delay estimation (JADE) for multipath signals arriving at an antenna array , 1997, IEEE Communications Letters.

[7]  Venkata N. Padmanabhan,et al.  Indoor localization without the pain , 2010, MobiCom.

[8]  Kaveh Pahlavan,et al.  Super-resolution TOA estimation with diversity for indoor geolocation , 2004, IEEE Transactions on Wireless Communications.

[9]  Kaveh Pahlavan,et al.  Modeling of the distance error for indoor geolocation , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[10]  Alok Aggarwal,et al.  Efficient, generalized indoor WiFi GraphSLAM , 2011, 2011 IEEE International Conference on Robotics and Automation.

[11]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  Juha-Pekka Makela,et al.  Indoor geolocation science and technology , 2002, IEEE Commun. Mag..

[13]  Jie Xiong,et al.  ArrayTrack: A Fine-Grained Indoor Location System , 2011, NSDI.

[14]  Petre Stoica,et al.  MUSIC, maximum likelihood and Cramer-Rao bound , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[15]  James Caffery,et al.  Hybrid TOA/AOA techniques for mobile location in non-line-of-sight environments , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[16]  Tom Minka,et al.  Precise indoor localization using PHY layer information , 2011, HotNets-X.