Skip to main content

Indoor Positioning in WiFi and NanoLOC Networks

  • Conference paper
  • First Online:
Internet of Things, Smart Spaces, and Next Generation Networks and Systems (ruSMART 2016, NEW2AN 2016)

Abstract

In this paper we compare the indoor positioning techniques of RToF in nanoLOC and RSSI fingerprinting in WiFi networks experimentally and highlight the impact of orientation during primary measurement acquisition for increasing location accuracy in the case of NLOS and multipath signal propagation conditions. Resulting accuracy estimates confirm known results and reveal that radiomap construction with primary RSSI measurements in four angular directions can improve positioning accuracy by 0.5 m in comparison with traditional fingerprinting in deployed WiFi and location dedicated nanoLOC networks.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bolliger, P.: Redpin-adaptive, zero-configuration indoor localization through user collaboration. In: Proceedings of the First ACM International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, Association of Computing Machinery, pp. 55–60 (2008)

    Google Scholar 

  2. SubPos a «Dataless» Open-Source WiFi positioning system. http://www.subpos.org/

  3. Real Time Location Systems. A White Paper from Nanotron Technologies GmbH, Version 1.02. http://nanotron.com/EN/pdf/WP_RTLS.pdf

  4. Röhrig, C., Müller, M.: Localization of sensor nodes in a wireless sensor network using the nanoLOC TRX transceiver. In: Vehicular Technology Conference, pp. 1–5. IEEE (2009)

    Google Scholar 

  5. Yim, J.: Comparison between RSSI-based and TOF-based indoor positioning methods. Int. J. Multimedia Ubiquit. Eng. 2, 221–234 (2012)

    Google Scholar 

  6. Galov, A., Moschevikin, A., Voronov, R.: Combination of RSS localization and ToF ranging for increasing positioning accuracy indoors. In: 11th International Conference on ITS Telecommunications (ITST), pp. 299–304. IEEE (2011)

    Google Scholar 

  7. Sivers, M., Fokin, G.: LTE positioning accuracy performance evaluation. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART 2015. LNCS, vol. 9247, pp. 393–406. Springer, Heidelberg (2015)

    Chapter  Google Scholar 

  8. Kireev, A., Fokin, G.: Radio direction finding of LTE emissions using mobile spectrum monitoring station with circular antenna array. Trudy Nauchno-issledovatel’skogo instituta radio, vol. 2, pp. 68–71 (2015). ISSN:0134-5583

    Google Scholar 

  9. Kolodziej, K.W., Hjelm, J.: Local Positioning Systems: LBS Applications and Services. CRC Press, Boca Raton (2006). pp. 102, 145, 151

    Book  Google Scholar 

  10. Blumenthal, J: Weighted centroid localization in zigbee-based sensor networks. In: Intelligent Signal Processing IEEE International Symposium, pp. 1–6. IEEE (2007)

    Google Scholar 

  11. Schuhmann, S., Herrmann, K., Rothermel, K., Blumenthal, J., Timmermann, D.: Improved weighted centroid localization in smart ubiquitous environments. In: Sandnes, F.E., Zhang, Y., Rong, C., Yang, L.T., Ma, J. (eds.) UIC 2008. LNCS, vol. 5061, pp. 20–34. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  12. Moka, E., Retscher, G.: Location determination using WiFi fingerprinting versus WiFi trilateration. J. Location Based Serv. 1(2), 145–159 (2007). Taylor & Francis

    Article  Google Scholar 

  13. Dmitriev, P., Pisarev, S., Sivers, M.: Analysis of methods and algorithms of positioning. In: Wifi Networks, vol. 10, p. 44. Vestnik Sviazy (2015). ISSN:0320–8141

    Google Scholar 

  14. Feng, J., Wang, Q.: Research of positioning technique based on wireless LAN. In: International Conference on Computer Science and Information Technology (ICCSIT 2011), vol. 51, pp. 202–207. IACSIT Press, Singapore (2012)

    Google Scholar 

  15. Liu, H., Darabi, H., Banerjee, P., Liu, J.: Survey of wireless indoor positioning techniques and systems. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37, 1067–1080 (2007). IEEE

    Article  Google Scholar 

  16. nanoPAN 5375 Development Kit User Guide Version 1.1 (2007). http://nanotron.com/EN/pdf/Factsheet_nanoPAN_5375_Dev_Kit.pdf

  17. WirelessMon software. http://www.passmark.com/products/wirelessmonitor.htm

  18. The MathWorks, Inc. http://www.mathworks.com

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Grigoriy Fokin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Sivers, M., Fokin, G., Dmitriev, P., Kireev, A., Volgushev, D., Hussein Ali, Ao.A. (2016). Indoor Positioning in WiFi and NanoLOC Networks. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NEW2AN 2016 2016. Lecture Notes in Computer Science(), vol 9870. Springer, Cham. https://doi.org/10.1007/978-3-319-46301-8_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46301-8_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46300-1

  • Online ISBN: 978-3-319-46301-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics