Skip to main content
Log in

A Comparative Study of Localization Methods in Indoor Environments

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

A comparative study, based on three different measurements (direction of ray arrival, time difference of arrival and received signal strength), to compute the unknown position of mobile stations in indoor environments is presented in this paper. The comparison is carried out considering the results of analyses in a real building in Madrid. To overcome the problems that arise in indoor areas due to the presence of non line of sight conditions, the fingerprinting technique is applied in each of the cases. Data for computations are provided by a simulation tool based on the uniform theory of diffraction and ray-tracing techniques. This information is stored in the fingerprinting database and contains information related to every mobile station, every reference node and every access point located inside the environment under analysis. Experimental results compare the mean error when localizing several mobile stations by using the three different approaches. The goal is to obtain high precision in the localization by means of alternative methods to the received signal strength classical measurement. These techniques will be useful in critical environments where high operational security requirement are demanded.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. Seow, C. K., & Tan, S. Y. (2008). Non line of sight localization in multipath environment. IEEE Transactions on Mobile Computing, 7, 647–660.

    Article  Google Scholar 

  2. Cong, L., & Zhuang, W. H. (2005). Non line-of-sight error mitigation in mobile location. IEEE Transactions on Wireless Communications, 4, 560–572.

    Article  Google Scholar 

  3. Fang, S.-H., Lin, T.-N., & Lee, K.-C. (2009). A novel algorithm for multipath fingerprinting in indoor WLAN environments. IEEE Transactions on Wireless Communications, 9, 3579–3588.

    Google Scholar 

  4. Seow, C. K., & Tan, S. Y. (2008). Localization of omni-directional mobile device in multipath environments. Progress In Electromagnetics Research, PIER, 85, 323–348.

    Article  Google Scholar 

  5. Sottile, F., Giannantonio, R., Spirito, M. A., & Bellifemine, F. L. (2008). Design deployment and performance of a complete real-time ZigBee localization system. Wireless Days, 1st IFIP, vol., no., 1–5, 24–27.

  6. Noh, A. S., Lee, I., & Ye, W. J. (2008). Comparison of the mechanisms of the Zigbee’s indoor localization algorithm. In Ninth international conference on software engineering, artificial intelligence, networking, and parallel, distributed computing, vol., no., 13–18.

  7. Koyuncu, H., & Yang, S. H. (2010). A survey of indoor positioning and object locating systems. IJCSNS International Journal of Computer Science and Network Security, 10(5), 121–128

    Google Scholar 

  8. Manapure, S. S., Darabi, H., Patel, V., & Banerjee, P. (2004). A comparative study of radio frequency-based indoor location sensing systems. IEEE International Conference on Networking, Sensing and Control, 2, 1265–1270.

    Article  Google Scholar 

  9. Vorst, P., Sommer, J., Hoene, C., Schneider, P., Weiss, C., Schairer, T. et al. (2008). Indoor positioning via three different RF technologies. In 4th European Workshop on RFID Systems and Technologies (RFID SysTech), (pp. 1,10).

  10. Hui, L., Darabi, H., Banerjee, P., & Jing, L. (2007). Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 37(6), 1067–1080.

    Article  Google Scholar 

  11. Yanying, G., Lo, A., & Niemegeers, I. (2009). A survey of indoor positioning systems for wireless personal networks. IEEE Communications Surveys and Tutorials, 11(1), 13–32.

    Article  Google Scholar 

  12. Brown, D. R., & Dunn, D. B. (2011). Classification schemes of positioning technologies for indoor navigation. In Proceedings of IEEE (pp. 125–130).

  13. Al Nuaimi, K., & Kamel, H. (2011). A survey of indoor positioning systems and algorithms. In International conference on innovations in information technology (IIT), pp. 185–190.

  14. Abdat, M., Tat-Chee W., & Supramaniam, S. (2010). Survey on indoor wireless positioning techniques: Towards adaptive systems. International conference on distributed framework and applications (DFmA), pp. 1–5.

  15. Hossain, A. K. M. M., Van, H. N., Yunye, J., & Soh, W. S. (2007). Indoor localization using multiple wireless technologies. IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems, MASS. (pp. 1–8).

  16. Besada, J. A., Bernardos, A. M., Tarrio, P., & Casar, J. R. (2007). Analysis of tracking methods for wireless indoor localization. International Symposium on Wireless Pervasive Computing, ISWPC ’07.

  17. Hatami, A., Alavi, B., Pahlavan, K., & Kanaan, M. (2006). A comparative performance evaluation of indoor geolocation technologies. Interdisciplinary Information Sciences, 12(2), 133–146.

    Article  Google Scholar 

  18. Honkavirta, V., Perala, T., Ali-Loytty, S., & Piche, R. (2009). A comparative survey of WLAN location fingerprinting methods. Workshop on Positioning, Navigation and Communication, WPNC, 2009, 243–251.

  19. Rodrigues, M. L., Vieira, L. F. M., & Campos, M. F. M. (2011). Fingerprinting-based radio localization in indoor environments using multiple wireless technologies. International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), pp. 1203–1207.

  20. Lin, T. N., & Lin, P. C. (2005). Performance comparison of indoor positioning techniques based on location fingerprinting in wireless networks. International Conference on Wireless Networks, Communications and Mobile Computing, 2, 1569–1574.

    Google Scholar 

  21. Seco, F., Jimenez, A. R., Prieto, C., Roa, J., & Koutsou, K. (2009). A survey of mathematical methods for indoor localization. IEEE International Symposium on Intelligent, Signal Processing, pp. 9–14.

  22. Priwgharm, R., & Chemtanomwong, P. (2011). A comparative study on indoor localization based on RSSI measurement in wireless sensor network. In International Joint Conference on Computer Science and Software Engineering (JCSSE) (pp. 1–6).

  23. Maher, P. S., & Malaney, R. A. (2009). A novel fingerprint location method using ray-tracing. Global Telecommunications Conference.

  24. Raspopoulos, M., Laoudias, C., Kanaris, L., Kokkinis, A., Panayiotou, C. G., & Stavrou, S. (Aug. 2012). Cross device fingerprint-based positioning using 3D ray tracing, 2012 8th International Wireless Communications and Mobile Computing Conference (IWCMC), (pp. 147,152, 27–31).

  25. Raspopoulos, M., Laoudias, C., Kanaris, L., Kokkinis, A., Panayiotou, C. G., & Stavrou, S. (March 2012). 3D ray tracing for device-independent fingerprint-based positioning in WLANs. 2012 9th Workshop on Positioning Navigation and Communication (WPNC), pp. 109,113, 15–16.

  26. Del Corte, A., Gomez, J. M., & Gutierrez, O. (2009). High precision for indoor localization applications based on relative delay and the fingerprinting technique. Third International Workshop on User-Centric Technologies and Applications vol. no., 25–32.

  27. newFASANT, Ray-tracing simulation tool, www.fasant.com.

  28. Saez de Adana, F., Gutierrez, O., Gonzalez, I., Perez, J., & Catedra, M. F. (2000). Propagation model based on ray-tracing for the design of personal communication systems in indoor environments. IEEE Transactions on Vehicular Technology vol. 49.

  29. Saez De Adana, F., Gutierrez, O., Gonzalez, I., Catedra, M. F., & Lozano, L. (2010). Practical applications of asymptotic techniques in electromagnetics. Artech House Publishers, chapter 6, pp. 149–207.

  30. Gutierrez, O., Saez de Adana, F., & Navarro, M. A. (2009). Efficient time-domain ray-tracing technique for the analysis of ultra-wideband indoor environments including lossy materials and multiple effects. International Journal on Antennas and Propagation.

  31. Saez de Adana, F., Gutierrez, O., Gonzalez, I., & Catedra, M. F. (2005). FASPRO: Fast computer tool for the analysis of propagation in mobile communications. IEEE International Conference on Industrial Informatics, INDIN ’05, pp. 257–261.

  32. Catedra, M. F., Perez, J., & Gutierrez, O. (1998). Efficient ray-tracing techniques for three-dimensional analyses of propagation in mobile communications: Application to picocell and microcell scenarios. IEEE Antennas and Propagation Magazine, 40(2), 15–28.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antonio del Corte.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gomez, J., Tayebi, A., del Corte, A. et al. A Comparative Study of Localization Methods in Indoor Environments. Wireless Pers Commun 72, 2931–2944 (2013). https://doi.org/10.1007/s11277-013-1189-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-013-1189-6

Keywords

Navigation