FMA-RRSS: Fingerprint Matching Algorithm Based on Relative Received Signal Strength in Indoor Wi-Fi Positioning

Indoor positioning based on Wi-Fi signal attracts a lot of attention in the location field. However, accuracy of positioning is often affected due to the instability of indoor Wi-Fi signal. In order to overcome this problem and reduce the errors, we present a new indoor WiFi-based positioning algorithm called FMA-RRSS which is the abbreviation of Fingerprint Matching Algorithm Based on Relative Received Strength Signal. In this paper, we propose a new position-determined model to produce location information from WiFi signal. Combined with the traditional solution of fingerprint database in indoor positioning, we use relative RSS value representing location information to estimate a clients actual position. We set up a positioning system and implement the FMA-RRSS in the actual WiFi environment. The experimental results show the improvement of positioning accuracy, fingerprint training complexity and response time of matching algorithm compared with other traditional indoor positioning algorithm like RADAR and Free Loc.

[1]  Hwee-Xian Tan,et al.  CIMLoc: A crowdsourcing indoor digital map construction system for localization , 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

[2]  Chong Wang,et al.  RFID-Based 3-D Positioning Schemes , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[3]  Henning Olesen,et al.  Bluetooth enables in-door mobile location services , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[4]  Yunhao Liu,et al.  WILL: Wireless indoor localization without site survey , 2012, 2012 Proceedings IEEE INFOCOM.

[5]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[6]  Michael R. Souryal,et al.  RFID-based localization and tracking technologies , 2011, IEEE Wireless Communications.

[7]  Mohammed Abdul Qadeer,et al.  GPS Locator: An Application for Location Tracking and Sharing Using GPS for Java Enabled Handhelds , 2011, 2011 International Conference on Computational Intelligence and Communication Networks.

[8]  Wang-Chien Lee,et al.  Rule-Based WiFi Localization Methods , 2008, 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.

[9]  Mario Gerla,et al.  FreeLoc: Calibration-free crowdsourced indoor localization , 2013, 2013 Proceedings IEEE INFOCOM.

[10]  Martin Vossiek,et al.  Wireless local positioning - concepts, solutions, applications , 2003, Radio and Wireless Conference, 2003. RAWCON '03. Proceedings.

[11]  Romit Roy Choudhury,et al.  EnLoc: Energy-Efficient Localization for Mobile Phones , 2009, IEEE INFOCOM 2009.

[12]  Shaojie Tang,et al.  Wi-Fi Fingerprint Based Indoor Localization without Indoor Space Measurement , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[13]  Yunhao Liu,et al.  LANDMARC: Indoor Location Sensing Using Active RFID , 2004, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[14]  Manuela M. Veloso,et al.  WiFi localization and navigation for autonomous indoor mobile robots , 2010, 2010 IEEE International Conference on Robotics and Automation.

[15]  Y. Ebihara.  Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[16]  Karl Andersson,et al.  Improving Wi-Fi based indoor positioning using Particle Filter based on signal strength , 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).