Short Range Indoor Distance Estimation by Using RSSI Metric

Year 2017, Volume: 17 Issue: 2, 3295 - 3302, 27.07.2017

Türker Türkoral , Özgür Tamer Suat Yetiş Enes İnanç Levent Çetin

https://izlik.org/JA68MW46RE

Abstract

In recent years, indoor localization
problem is a highly preferred topic to study. In order to estimate the relative
positions of the communication nodes in a localization system, the distance
information of each node is required. In this paper, it is aimed to estimate
the distances between the nodes by using the received signal strength (RSS)
measurements. For an indoor environment, with the RSS based distance estimation
methods, the short range distances between the nodes can be estimated by using
the Received Signal Strength Indicator (RSSI) measurements taken over a
standard wireless communication infrastructure, namely Wi-Fi.

Keywords

Indoor distance estimation , RSSI

References

• Güvenç, I., & Chong, C. C. (2009). A survey on TOA based wireless localization and NLOS mitigation techniques. IEEE Communications Surveys and Tutorials, 11(3), 107–124.
• Doǧançay, K. (2005). Emitter localization using clustering-based bearing association. IEEE Transactions on Aerospace and Electronic Systems, 41(2), 525–536.
• Arslan, H., Chen, Z. N., & Di Benedetto, M.-G. (Eds.). (2006). Ultra wideband wireless communication. New Jersey. John Wiley & Sons.
• Laaraiedh, M., Yu, L., Avrillon, S., & Uguen, B. (2011). Comparison of hybrid localization schemes using RSSI, TOA and TDOA. European Wireless, 2011, 626–630.
• Hara, S., & Anzai, D. (2008). Experimental Performance Comparison of RSSI- and TDOA-Based Location Estimation Methods. VTC Spring 2008 - IEEE Vehicular Technology Conference, 0, 2651–2655.
• Türkoral, T., Tamer, Ö., Yetiş, S., İnanç, E., & Çetin, L. (2016). Alınan işaret güç göstergesi (RSSI) metriği kullanılarak kapalı alan mesafe kestirimi. (yayınlanmamış) Elektrik-Elektronik ve Biyomedikal Mühendisliği Konferansı, 2016.
• Xiao, J., Liu, Z., Yang, Y., Liu, D., & Xu, H. (2011). Comparison and analysis of indoor wireless positioning techniques. 2011 International Conference on Computer Science and Service System, CSSS 2011 - Proceedings, 293–296.
• Chrysikos, T., Georgopoulos, G., & Kotsopoulos, S. (2009). Site-specific validation of ITU indoor path loss model at 2.4 GHz. 2009 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks and Workshops, WOWMOM 2009.
• Lassabe, F., Canalda, P., Chatonnay, P., Spies, F., & Baala, O. (2005). A Friis-based calibrated model for WiFi terminals positioning. Proceedings - 6th IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks, WoWMoM 2005, 382–387.
• Sommer, C., & Dressler, F. (2011). Using the right two-ray model? A Measurement based evaluation of PHY models in VANETs. Proceeding ACM MobiCom, (3), 1–3.
• International Telecommunication Union. (2015). Retrieved January 10, 2017, from https://www.itu.int/dms_pubrec/itu-r/rec/p/R-REC-P.1238-8-201507-I!!PDF-E.pdf
• Seybold, J. S. (2005). Introduction to RF Propagation. John Wiley & Sons, Inc. New Jersey, US.
• FN-LINK. (n.d.). Realtek RTL8723BU USB Wi-Fi+BT Combo Module. Retrieved January 7, 2017, from http://www.fn-link.com/downloadRepository/113cd977-6c9-1-4f69-8b97-63fc138fa254.pdf
• Rappaport, T. S., Reed, J. H., & Woerner, B. D. (1996). Position location using wireless communications on highways of the future. IEEE Communications Magazine, 34(10), 33–41.
• Taoglas Antenna Solutions. (2011). Retrieved 20 September 2016 from http://www.taoglas.com/images/product_images/original_images/GW.26.0111%202.4GHz%20Band%20Monopole%20SMA(M).pdf