Nothing Special   »   [go: up one dir, main page]

skip to main content
article

Automatic virtual calibration of range-based indoor localization systems

Published: 01 December 2012 Publication History

Abstract

The localization methods based on received signal strength indicator (RSSI) link the RSSI values to the position of the mobile to be located. In the RSSI localization techniques based on propagation models, the accuracy depends on the tuning of the propagation models parameters. In indoor wireless networks, the propagation conditions are hardly predictable due to the dynamic nature of the RSSI, and consequently the parameters of the propagation model may change. In this paper, we present an automatic virtual calibration method of the propagation model that does not require human intervention; therefore, can be periodically performed, following the wireless channel conditions. We also propose a novel RSSI-based localization algorithm that selects the RSSI values according to their strength, and uses a calibrated propagation model to transform these values into distances, in order to estimate the position of the mobile. Copyright © 2011 John Wiley & Sons, Ltd.
(We propose an automatic calibration procedure of the signal propagation model that is only based on the RSSIs measured among the anchors and that can be executed periodically and automatically (i.e., without human intervention). Based on the virtual calibration procedure, we propose a localization algorithm that selects the anchors with higher signal strength, and it exploits the calibrated propagation model to relate RSSI measures with distances. Finally, in order to provide the mobile position, the algorithm uses a trilateration method.)

References

[1]
Want R, Hopper A, Falcao V, Gibbons J. The active badge location system. ACM Transactions on Information Systems 1992; 10(1): 91–102.
[2]
Abowd GD, Atkeson CG, Hong J, Long S, Kooper R, Pinkerton M. Cyberguide: a mobile context-aware tour guide. Wireless Networks 1997; 3(5): 421–433.
[3]
Sumi Y, Etani T, Fels S, Simonet N, Kobayashi K, Mase K. C-map: Building a context-aware mobile assistant for exhibition tours. Community Computing and Support Systems, Lecture Notes in Computer Science. Springer-Verlag: London, UK, 1998; 1519: 137–154.
[4]
Cheverst K, Davies N, Mitchell K, Friday A, Efstratiou C. Developing a context-aware electronic tourist guide: some issues and experiences. Proceedings of the SIGCHI conference on Human factors in computing systems (CHI '00), ACM Press, New York, NY, USA 2000; 17–24.
[5]
Baronti P, Pillai P, Chook VWC, Chessa S, Gotta A, Hu YF. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Computer Communications 2007; 30(7): 1655–1695.
[6]
Giorgetti G, Gupta SKS, Manes G. Localization using signal strength: to range or not to range? MELT '08: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments, ACM New York, NY, USA 2008; 91–96.
[7]
Elnahrawy E, Li X, Martin RP. The limits of localization using signal strength: A comparative study. First IEEE International Conference on Sensor and Ad hoc Communications and Networks (SECON 2004), New York, NY, USA 2004; 41–52.
[8]
Patwari N, Hero IAO, Perkins M, Correal N, O'Dea R. Relative location estimation in wireless sensor networks. IEEE Transactions on Signal Processing 2003; 51(8): 2137–2148.
[9]
Bergamo P, Mazzini G. Localization in sensor networks with fading and mobility. 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Vol. 2, 2002; 750–754.
[10]
Yu K, Guo Y. Anchor-free localisation algorithm and performance analysis in wireless sensor networks. IET Communications 2009; 3(4): 549–560.
[11]
Christ T, Godwin P, Lavigne R. A prison guard duress alarm location system. International Carnahan Conference on Security Technology, 1993; 106–116.
[12]
Lorincz K, Welsh M. Motetrack: a robust, decentralized approach to RF-based location tracking. Personal and Ubiquitous Computing 2006; 11(6): 489–503.
[13]
King T, Kopf S, Haenselmann T, Lubberger C, Effelsberg W. Compass: a probabilistic indoor positioning system based on 802.11 and digital compasses. Proceedings of the First ACM International Workshop on Wireless Network Testbeds, Experimental evaluation and Characterization (WiNTECH), Los Angeles, CA, USA 2006.
[14]
Youssef M, Agrawala A. The WLAN location determination system. MobiSys '05: Proceedings of the 3rd international conference on Mobile systems, applications, and services, ACM: New York, NY, USA 2005; 205–218.
[15]
Papapostolou A, Chaouchi H. Wife: wireless indoor positioning based on fingerprint evaluation. 8th International IFIP-TC 6 Networking Conference 2009; 234–247.
[16]
Bahl P, Padmanabhan V. Radar: an in-building RF-based user location and tracking system. INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE Vol. 2, 2000; 775–784.
[17]
An X, Wang J, Prasad RV, Niemegeers IGMM. Opt: online person tracking system for context-awareness in wireless personal network. Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality (REALMAN '06), ACM: New York, NY, USA 2006; 47–54.
[18]
Yeung WM, Zhou J, Ng JK. Enhanced fingerprint-based location estimation system in wireless LAN environment. EUC Workshops, 2007; 4809: 273–284.
[19]
Bulusu N, Heidemann J, Estrin D. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications 2000; 7(5): 28–34.
[20]
Gwon Y, Jain R, Kawahara T. Robust indoor location estimation of stationary and mobile users. 2004; 1032–1043.
[21]
Manodham T, Loyola L, Miki T. A novel wireless positioning system for seamless internet connectivity based on the WLAN infrastructure. Wireless Personal Communications 2008; 44(3): 295–309.
[22]
Mazuelas S, Bahillo A, Lorenzo R, et al. Robust indoor positioning provided by real-time RSSI values in unmodified WLAN networks. IEEE Journal of Selected Topics in Signal Processing 2009; 3(5): 821–831.
[23]
Green E, Hata M. Microcellular propagation measurements in an urban environment. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications 1991; 324–328.
[24]
Borrelli A, Monti C, Vari M, Mazzenga F. Channel models for IEEE 802.11b indoor system design. IEEE International Conference on Communications, 6, 2004; 3701–3705.
[25]
Crossbow Technology, Inc., http://www.xbow.com
[26]
Lymberopoulos D, Lindsey Q, Savvides A. An empirical characterization of radio signal strength variability in 3-D IEEE 802.15.4 networks using monopole antennas. Third European Workshop Wireless Sensor Networks (EWSN '06) 2006; 326–341.
[27]
Bjorck A. Solution of Equations in RN, Least Squares Methods: Handbook of Numerical Analysis, Vol. 1, Elsevier: NorthHolland, 1990.
[28]
Rappaport TS. Wireless Communication: Principles and Practice (2nd edn), Prentice Hall: 2001.
[29]
Linnartz JPM. Indoor Propagation at 2.4 GHz. URL: http://www.wirelesscommunication.nl/reference/chaptr03/2_4ghz.htm.
[30]
Barsocchi P, Lenzi S, Chessa S, Giunta G. Virtual calibration for RSSI-based indoor localization with IEEE 802.15.4. IEEE International Conference on Communications (ICC '09) 2009; 1–5.
[31]
Barsocchi P, Lenzi S, Chessa S, Giunta G. A novel approach to indoor RSSI localization by automatic calibration of the wireless propagation model. IEEE 69th Vehicular Technology Conference (VTC Spring 2009) 2009; 1–5.

Cited By

View all
  • (2017)Dealing with Insufficient Location Fingerprints in Wi-Fi Based Indoor Location FingerprintingWireless Communications & Mobile Computing10.1155/2017/12685152017Online publication date: 1-Jan-2017
  • (2017)Evaluating the impact of smart technologies on harbor's logistics via BPMN modeling and simulationInformation Technology and Management10.1007/s10799-016-0266-418:3(223-239)Online publication date: 1-Sep-2017
  1. Automatic virtual calibration of range-based indoor localization systems

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image Wireless Communications & Mobile Computing
    Wireless Communications & Mobile Computing  Volume 12, Issue 17
    December 2012
    88 pages

    Publisher

    John Wiley and Sons Ltd.

    United Kingdom

    Publication History

    Published: 01 December 2012

    Author Tags

    1. calibration parameters
    2. indoor localization
    3. indoor propagation model
    4. wireless sensor network

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 14 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2017)Dealing with Insufficient Location Fingerprints in Wi-Fi Based Indoor Location FingerprintingWireless Communications & Mobile Computing10.1155/2017/12685152017Online publication date: 1-Jan-2017
    • (2017)Evaluating the impact of smart technologies on harbor's logistics via BPMN modeling and simulationInformation Technology and Management10.1007/s10799-016-0266-418:3(223-239)Online publication date: 1-Sep-2017

    View Options

    View options

    Get Access

    Login options

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media