Indoor Localization with Low Complexity in Wireless Sensor Networks

Autonomous localization of nodes in wireless sensor networks is essential to minimize the complex self organization task consequently enhancing the overall network lifetime. Recently, precise indoor localization is impeded by multi path propagation of signals due to reflections at walls or objects. In this paper we partly overcome some of these problems by methods like frequency diversity and averaging multiple measured data. Received radio signal strength (RSS) in combination with weighted centroid localization, featuring low communication overhead and a low complexity of O(n), is our basis of a localization on the energy constrained sensor nodes. We first analyze the RSS-characteristics on a specific sensor node platform in different rooms. Next, we describe methods to improve these characteristics to reach best localization results at minimized complexity. Finally, in a practice indoor localization we achieve a small localization error of only 14% for 69% of all test-points that was enhanced to at least 8% in average by simple optimizations. For that, no hardware modifications as well as time consuming RSSI-maps or complex signal propagation models are required.

[1]  Srdjan Capkun,et al.  GPS-free Positioning in Mobile Ad Hoc Networks , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[2]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[4]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.

[5]  Anantha Chandrakasan,et al.  Low-power wireless sensor networks , 2001, VLSI Design 2001. Fourteenth International Conference on VLSI Design.

[6]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[7]  Dirk Timmermann,et al.  Position Estimation in Ad hoc Wireless Sensor Networks with Low Complexity , 2005 .

[8]  Bhaskar Krishnamachari,et al.  Ecolocation: a sequence based technique for RF localization in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[9]  Carlos J. Escudero,et al.  In-building location using Bluetooth , 2005 .

[10]  Gang Zhou,et al.  Impact of radio irregularity on wireless sensor networks , 2004, MobiSys '04.

[11]  Sebastian Thrun,et al.  A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data , 2003, IJCAI.

[12]  Poster Abstract : The Limits of Localization Using RSS , 2004 .

[13]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[14]  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).

[15]  L. El Ghaoui,et al.  Convex position estimation in wireless sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[16]  Alfred O. Hero,et al.  Using proximity and quantized RSS for sensor localization in wireless networks , 2003, WSNA '03.

[17]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[18]  Dirk Timmermann,et al.  Precise Positioning with a Low Complexity Algorithm in Ad hoc Wireless Sensor Networks , 2005, Prax. Inf.verarb. Kommun..

[19]  Gaetano Borriello,et al.  SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength , 2000 .

[20]  Andreas Savvides,et al.  An Empirical Characterization of Radio Signal Strength Variability in 3-D IEEE 802.15.4 Networks Using Monopole Antennas , 2006, EWSN.

[21]  Yu Wang,et al.  Towards an indoor location system using RF signal strength in IEEE 802.11 networks , 2005, International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II.