Indoor positioning using differential Wi-Fi lateration
-
Guenther Retscher
and
Thomas Tatschl
Abstract
For Wi-Fi positioning usually location fingerprinting or (tri)lateration are employed whereby the received signal strengths (RSSs) of the surrounding Wi-Fi Access Points (APs) are scanned on the mobile devices and used to perform localization. Within the scope of this study, the position of a mobile user is determined on the basis of lateration. Two new differential approaches are developed and compared to two common models, i.e., the one-slope and multi-wall model, for the conversion of the measured RSS of the Wi-Fi signals into ranges. The two novel methods are termed DWi-Fi as they are derived either from the well-known DGPS or VLBI positioning principles. They make use of a network of reference stations deployed in the area of interest. From continuous RSS observations on these reference stations correction parameters are derived and applied by the user in real-time. This approach leads to a reduced influence of temporal and spatial variations and various propagation effects on the positioning result. In practical use cases conducted in a multi-storey office building with three different smartphones, it is proven that the two DWi-Fi approaches outperform the common models as static positioning yielded to position errors of about 5 m in average under good spatial conditions.
References
[1] Avenau L, Masson E, Combeau P (2010) RaPSor: a Radio Propagation Simulator, Presentation and Use Cases. Product Presentation, acessed March 27, 2017 at https://www.researchgate.net/publication/228735225_RaPSor_a_Radio_Propagation_Simulator_Presentation_and_Use_Cases.Search in Google Scholar
[2] Durgin G, Patwari N, Rappaport T S (1997) An Advanced 3D Ray Launching Method for Wireless Propagation Prediction. IEEE 47th Vehicular Technology Conference, Phoenix, Arizona, USA, 785–789.10.1109/VETEC.1997.600436Search in Google Scholar
[3] Hofer H, Retscher G. (2016) Combined Out- and Indoor Navigation with Smart Phones Using Intelligent Check Points. 13th International Symposium on Location-Based Services LBS 2016, November 14–16, 2016, Vienna, Austria, 82–90.Search in Google Scholar
[4] Kaemarungsi K, Krishnamurthy P (2004) Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting. Mobile and Ubiquitous Systems: Networking and Services MOBIQUITOUS 2004, 14–23.10.1109/MOBIQ.2004.1331706Search in Google Scholar
[5] Landau H, Vollath U, Chen X (2002) Virtual Reference Station Systems. Journal of Global Positioning Systems, 1:2, 137–143.10.5081/jgps.1.2.137Search in Google Scholar
[6] Luntovskyy A, Gütter D, Melnyk I (2012) Planung und Optimierung von Rechnernetzen. Springer Science and Business Media (in German).10.1007/978-3-8348-8242-4Search in Google Scholar
[7] Metter M, Bucher R (2007) Industrial Ethernet in der Automatisierungstechnik: Planung und Einsatz von Ethernet-LAN-Techniken im Umfeld von SIMATIC-Produkten, Publicis Corporate Publishing, 2nd edition, Erlangen, Germany (in German).Search in Google Scholar
[8] Ramlow S, Peterhanwahr J (2008) Industrial Wireless. Dr.-Ing. Paul Christiani GmbH & Co KG, 1st edition, Konstanz, Germany.Search in Google Scholar
[9] Retscher G, Hofer H. (2017) Wi-Fi Location Fingerprinting Using an Intelligent Checkpoint Sequence. Journal of Applied Geodesy, 11:3, 197–205.10.1515/jag-2016-0030Search in Google Scholar
[10] Retscher G, Roth F (2017) Wi-Fi Fingerprinting with Reduced Signal Strength Observations from Long-time Measurements. In: Gartner G, Huang H (eds.) Progress in Location-Based Services 2016, Lecture Notes in Geoinformation and Cartography, ISBN 978-3-319-47289-8, DOI 10.1007/978-3-319-47289-8_1, 3-24.Search in Google Scholar
[11] Schuh W-D (1984) Rasche und einfache automatische Fehlererkennung bei großen Datenmengen. Österreichische Zeitschrift für Vermessungswesen, 72:4, 137–147 (in German).Search in Google Scholar
[12] Wanninger L (2002) Virtual Reference Stations for Centimeter-Level Kinematic Positioning. ION GPS 2002, Portland, Oregeon, USA, 1400–1407.Search in Google Scholar
© 2017 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- Effect of coseismic and postseismic deformation on homogeneous and layered half-space and spherical analysis: Model simulation of the 2006 Java, Indonesia, tsunami earthquake
- Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation
- Towards the Moho depth and Moho density contrast along with their uncertainties from seismic and satellite gravity observations
- Indoor positioning using differential Wi-Fi lateration
- Congruence analysis of geodetic networks – hypothesis tests versus model selection by information criteria
Articles in the same Issue
- Frontmatter
- Research Articles
- Effect of coseismic and postseismic deformation on homogeneous and layered half-space and spherical analysis: Model simulation of the 2006 Java, Indonesia, tsunami earthquake
- Statistical evaluation of the influence of the uncertainty budget on B-spline curve approximation
- Towards the Moho depth and Moho density contrast along with their uncertainties from seismic and satellite gravity observations
- Indoor positioning using differential Wi-Fi lateration
- Congruence analysis of geodetic networks – hypothesis tests versus model selection by information criteria
