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Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration

Received: 12 November 2014    Accepted: 16 November 2014    Published: 27 November 2014
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Abstract

In this paper, Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indoor environment. Various testing scenarios have been examined for comparison of the two methods, as the performance level in RF Fingerprinting is mainly depend on the number of modems, as well as the density of training data and, the multilateration method is mainly depend on correctly modeling of the path loss exponent. Optimizing and defining a unique path loss exponent for each of the wireless transmitter modems, testing in a LoS and a nLoS medium, changing the number of transmitters, etc, have been tried and performance plots have been shown for comparison purposes.

Published in Communications (Volume 2, Issue 2)
DOI 10.11648/j.com.20140202.11
Page(s) 15-21
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Indoor Localization, RSS (Receive Signal Strength), Lateration Technique, Wi-Fi Based Localization, LBS, RF Fingerprinting, Signal Strength to Distance Conversion

References
[1] J. Schiller and A.Voisard, “Location Based Services”, Morgan Kaufmann Puv,2004.
[2] NICULESCU, D., BADRI, N. Ad hoc positioning system (APS) using AOA. In Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2003. San Francisco (USA), 2003, p. 1734 – 1743.
[3] B. Lee, String field theory,Hasan Buyruk, A.Kenan Keskin,Şeyma Şendil,Hasari Çelebi,Hakan P.Partal,Salih Ergut,Engin Zeydan,and omer Ileri, “RF Fingerprinting Based GSM Indoor Localization”, Signal Processing and Communications Applications Conference,SIU,2013.
[4] A Ward, A Jones, A Hopper, “A New Location Technique for Active Office”, IEEE Personal Communications, Vol 4, No 5, Oct 1997.
[5] SAYED, A. H., TARIGHAT, A., KHAJEHNOURI, N. Network based wireless location: challenges faced in developing techniques for accurate wireless location information. IEEE Signal Processing Magazine, 2005, vol. 22, no. 4, p. 24 – 40.
[6] Ugur Alkasi, Md Al Shayokh , Hakan P. Partal, “An experimental comparison study on indoor localization: RF fingerprinting and multilateration methods,” 10th international Conference on electronics, Computer and Computation, Ankara, Turkey, Nov. 7-9, 2013.
[7] Li,B.,Kam,J.,Lui,I.,& Dempstar,A.(2007). Use of Directional Information in Wireless LAN based indoor positioning. Proceedings of IGNSS (International Global Navigation Satellite Systems Society) Symposium.Taipei:IEEE.
[8] Paramvir Bahl and Venkata N. Padmanabhan, "RADAR: an In-building RF-based User Location and Tracking System," in Joint Conference of the IEEE Computer and Communications Societies, vol. 2, 2000, pp. 775-784.
[9] Jeff Thurston, "GALILEO, GLONASS And NAVSTAR A Report on GPS for GIS People," GISCafe.com, 2002.
[10] Vasileios Zeimpekis, George M. Giaglis, and George Lek, "A taxonomy of indoor and outdoor positioning techniques for mobile location services," SIGecom Exchange, 2003.
[11] Bill R, Cap C, Kofahl M, and Mundt T, "Indoor and Outdoor Positioning in Mobile Environments," Geographical Information Sciences, pp. 91-98, 2004.
[12] Chiou, Y., C. Wang, S. Yeh & M. Su, “Design of an adaptive positioning system based on WiFi radio signals”. Computer Communications 32, pp. 1245-1254, 2009.
[13] http://www.bluetooth.com/Bluetooth/Technology/Works/
[14] Sinan Gezici et al., "Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks," IEEE in Signal Processing Magazine, vol. 22, no. 4, pp. 70-84, 2005.
[15] Jeffrey R. Foerster et al. “A Channel Model for Ultrawideband Indoor Communication”, 2003.
[16] Woo et al. (2011), Application of Wi-Fi-based indoor positioning system for labor tracking at construction sites: A case study in Guangzhou MTR. Automation in construction 20, pp. 3-13.
[17] Kolodziej, K. & J. Hjelm (2006), Local Positioning Systems. LBS Applications and Services. Boca Raton, FL, USA: CRC Press – Taylor & Francis Group.
[18] Zhang, D. et al., “Localization Technologies for Indoor Human Tracking”. Paper submitted to the 5th International Conference on Future Information Technology (FutureTech), May 2010, Busan, Korea.
[19] http://www.convep.com/malls.html
[20] Kamol Kaemarungsi and Prashant Krishnamurthy, "Modeling of Indoor Positioning Systems Based on Location Fingerprinting," 2004.
Cite This Article
  • APA Style

    Md. Al Shayokh, Ugur Alkasi. (2014). Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration. Communications, 2(2), 15-21. https://doi.org/10.11648/j.com.20140202.11

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    ACS Style

    Md. Al Shayokh; Ugur Alkasi. Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration. Communications. 2014, 2(2), 15-21. doi: 10.11648/j.com.20140202.11

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    AMA Style

    Md. Al Shayokh, Ugur Alkasi. Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration. Communications. 2014;2(2):15-21. doi: 10.11648/j.com.20140202.11

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  • @article{10.11648/j.com.20140202.11,
      author = {Md. Al Shayokh and Ugur Alkasi},
      title = {Experimental Performance Analysis and Improvement Techniques for RSSI Based Indoor Localization: RF Fingerprinting and RF Multilateration},
      journal = {Communications},
      volume = {2},
      number = {2},
      pages = {15-21},
      doi = {10.11648/j.com.20140202.11},
      url = {https://doi.org/10.11648/j.com.20140202.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.com.20140202.11},
      abstract = {In this paper, Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indoor environment. Various testing scenarios have been examined for comparison of the two methods, as the performance level in RF Fingerprinting is mainly depend on the number of modems, as well as the density of training data and, the multilateration method is mainly depend on correctly modeling of the path loss exponent. Optimizing and defining a unique path loss exponent for each of the wireless transmitter modems, testing in a LoS and a nLoS medium, changing the number of transmitters, etc, have been tried and performance plots have been shown for comparison purposes.},
     year = {2014}
    }
    

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    AU  - Md. Al Shayokh
    AU  - Ugur Alkasi
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    N1  - https://doi.org/10.11648/j.com.20140202.11
    DO  - 10.11648/j.com.20140202.11
    T2  - Communications
    JF  - Communications
    JO  - Communications
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    PB  - Science Publishing Group
    SN  - 2328-5923
    UR  - https://doi.org/10.11648/j.com.20140202.11
    AB  - In this paper, Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indoor environment. Various testing scenarios have been examined for comparison of the two methods, as the performance level in RF Fingerprinting is mainly depend on the number of modems, as well as the density of training data and, the multilateration method is mainly depend on correctly modeling of the path loss exponent. Optimizing and defining a unique path loss exponent for each of the wireless transmitter modems, testing in a LoS and a nLoS medium, changing the number of transmitters, etc, have been tried and performance plots have been shown for comparison purposes.
    VL  - 2
    IS  - 2
    ER  - 

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Author Information
  • Department of ECE, Yildiz Technical University, Esenler, Istanbul, Turkey

  • Department of ECE, Yildiz Technical University, Esenler, Istanbul, Turkey

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