Abstract
Knowing the location of Wi-Fi antennas may be critical for indoor localization. However, in a real environment, their positions may be unknown since they can be managed by external entities. This paper introduces a new method for evaluating the suitability of using the weighted centroid method for the 2D localization of a Wi-Fi AP. The method is based on the idea that the weighted centroid method provides its best results when there are fingerprints taken around the AP. In order to find the probability of being in the presence of such situations, a natural neighbor interpolation method is used to find the regions with the highest signal strengths. A geometrical method is then used to characterize that probability based on the distribution of those regions in relation to the AP position estimation given by the weighted centroid method. The paper describes the testing location and the used Wi-Fi fingerprints database. That database is used to create new databases that recreate different sampling possibilities through a samples deletion strategy. The original database and the newly created ones are then used to evaluate the localization results of several AP localization methods and the new method proposed in this paper. The evaluation results have shown that the proposed method is able to provide a proper probability for the suitability of using the weighted centroid method for localizing a Wi-Fi AP.
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Notes
- 1.
https://wigle.net/, visited on 10/06/16.
- 2.
As implemented in Matlab.
- 3.
Available at http://indoorloc.uji.es, visited on 10/06/16.
References
Al-Ammar, M. A., Alhadhrami, S., Al-Salman, A., Alarifi, A., Al-Khalifa, H. S., Alnafessah, A., & Alsaleh, M. (2014). Comparative Survey of Indoor Positioning Technologies, Techniques, and Algorithms. In Cyberworlds (CW), 2014 International Conference on (pp. 245–252). http://doi.org/10.1109/CW.2014.41.
Arai, K., & Tolle, H. (2013). Color radiomap interpolation for efficient fingerprint wifi-based indoor location estimation. International Journal of Advanced Research in Artificial Intelligence, 2(3), 10–15.
Bahl, P., & Padmanabhan, V. N. (2000). RADAR: An in-building RF-based user location and tracking system. In INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE (Vol. 2, pp. 775–784).
Berghel, H. (2004). Wireless infidelity I: War driving. Communications of the ACM, 47(9), 21–26.
Blumenthal, J., Grossmann, R., Golatowski, F., & Timmermann, D. (2007). Weighted Centroid Localization in Zigbee-based Sensor Networks. In Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on (pp. 1–6). http://doi.org/10.1109/WISP.2007.4447528.
Chen, G., & Kotz, D. (2000). A Survey of Context-Aware Mobile Computing Research. Hanover, NH, USA: Dartmouth College.
Cheng, Y.-C., Chawathe, Y., LaMarca, A., & Krumm, J. (2005). Accuracy Characterization for Metropolitan-scale Wi-Fi Localization. In Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services (pp. 233–245). New York, NY, USA: ACM. http://doi.org/10.1145/1067170.1067195.
Cho, Y., Ji, M., Lee, Y., Kim, J., & Park, S. (2012). Improved Wi-Fi AP position estimation using regression based approach. In Proc. of the International Conference on Indoor Positioning and Indoor Navigation.
Cho, Y., Ji, M., Lee, Y., & Park, S. (2012). WiFi AP position estimation using contribution from heterogeneous mobile devices. In Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION (pp. 562–567). http://doi.org/10.1109/PLANS.2012.6236928.
Ezpeleta, S., Claver, J., Pérez-Solano, J., & Martí, J. (2015). RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping. Sensors, 15(10), 27322–27340. http://doi.org/10.3390/s151027322.
Farid, Z., Nordin, R., & Ismail, M. (2013). Recent advances in wireless indoor localization techniques and system. Journal of Computer Networks and Communications, 2013.
Gutmann, J.-S., Burgard, W., Fox, D., & Konolige, K. (1998). An experimental comparison of localization methods. In Intelligent Robots and Systems, 1998. Proceedings., 1998 IEEE/RSJ International Conference on (Vol. 2, pp. 736–743 vol.2). http://doi.org/10.1109/IROS.1998.727280.
Han, D., Andersen, D. G., Kaminsky, M., Papagiannaki, K., & Seshan, S. (2009). Access Point Localization Using Local Signal Strength Gradient. In S. B. Moon, R. Teixeira, & S. Uhlig (Eds.), Passive and Active Network Measurement: 10th International Conference, PAM 2009, Seoul, Korea, April 1–3, 2009. Proceedings (pp. 99–108). Berlin, Heidelberg: Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-00975-4_10.
Ji, M., Kim, J., Cho, Y., Lee, Y., & Park, S. (2013). A novel Wi-Fi AP localization method using Monte Carlo path-loss model fitting simulation. In 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 3487–3491). http://doi.org/10.1109/PIMRC.2013.6666752.
Knauth, S., Storz, M., Dastageeri, H., Koukofikis, A., & Mähser-Hipp, N. A. (2015). Fingerprint calibrated centroid and scalar product correlation RSSI positioning in large environments. In Indoor Positioning and Indoor Navigation (IPIN), 2015 International Conference on (pp. 1–6). http://doi.org/10.1109/IPIN.2015.7346968.
Koo, J., & Cha, H. (2011a). Autonomous construction of a WiFi access point map using multidimensional scaling. In Pervasive Computing (pp. 115–132). Springer.
Koo, J., & Cha, H. (2011b). Localizing WiFi access points using signal strength. IEEE Communications Letters, 15(2), 187–189. http://doi.org/10.1109/LCOMM.2011.121410.101379.
Koo, J., & Cha, H. (2012). Unsupervised locating of WiFi access points using smartphones. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 42(6), 1341–1353.
Kosović, I. N., & Jagušt, T. (2014). Enhanced Weighted Centroid Localization Algorithm for Indoor Environments. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 8(7), 1184–1188.
Ledlie, J., g. Park, J., Curtis, D., Cavalcante, A., Camara, L., Costa, A., & Vieira, R. (2011). Mole: A scalable, user-generated WiFi positioning engine. In Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on (pp. 1–10). http://doi.org/10.1109/IPIN.2011.6071942.
Lee, M., & Han, D. (2012). Voronoi Tessellation Based Interpolation Method for Wi-Fi Radio Map Construction. IEEE Communications Letters, 16(3), 404–407. http://doi.org/10.1109/LCOMM.2012.020212.111992.
Liu, H., Darabi, H., Banerjee, P., & Liu, J. (2007). Survey of Wireless Indoor Positioning Techniques and Systems. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 37(6), 1067–1080. http://doi.org/10.1109/TSMCC.2007.905750.
Liu, H.-H., & Yang, Y.-N. (2012). Study on the use of a weighted screening method for indoor positioning systems. In The 15th International Symposium on Wireless Personal Multimedia Communications.
Lohan, E. S., Talvitie, J., e Silva, P., Nurminen, H., Ali-Loytty, S., & Piche, R. (2015). Received signal strength models for WLAN and BLE-based indoor positioning in multi-floor buildings. In Localization and GNSS (ICL-GNSS), 2015 International Conference on (pp. 1–6).
Maple, C. (2003). Geometric design and space planning using the marching squares and marching cube algorithms. In Geometric Modeling and Graphics, 2003. Proceedings. 2003 International Conference on (pp. 90–95). http://doi.org/10.1109/GMAG.2003.1219671.
Moreira, A., & Meneses, F. (2015). Where@UM - Dependable organic radio maps. In Indoor Positioning and Indoor Navigation (IPIN), 2015 International Conference on (pp. 1–9). http://doi.org/10.1109/IPIN.2015.7346751.
Nam, S. Y. (2014). Localization of Access Points Based on Signal Strength Measured by a Mobile User Node. Communications Letters, IEEE, 18(8), 1407–1410.
Savvides, A., Han, C.-C., & Strivastava, M. (2001). Dynamic fine-grained localization in Ad-Hoc networks of sensors. Proceeding MobiCom ’01 Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, 166–179. http://doi.org/10.1145/381677.381693.
Sibson, R., & others. (1981). A brief description of natural neighbour interpolation. Interpreting Multivariate Data, 21, 21–36.
Talvitie, J., Renfors, M., & Lohan, E. S. (2015). Distance-Based Interpolation and Extrapolation Methods for RSS-Based Localization With Indoor Wireless Signals. IEEE Transactions on Vehicular Technology, 64(4), 1340–1353. http://doi.org/10.1109/TVT.2015.2397598.
Torres-Solis, J., Falk, T. H., & Chau, T. (2010). A review of indoor localization technologies: towards navigational assistance for topographical disorientation. INTECH Open Access Publisher.
Torres-Sospedra, J., Montoliu, R., Mendoza, G., Belmonte, O., Rambla, D., & Huerta, J. (2016). Providing Databases for Different Indoor Positioning Technologies: Pros and Cons of Magnetic field and Wi-Fi based Positioning. Mobile Information Systems.
Varzandian, S., Zakeri, H., & Ozgoli, S. (2013). Locating WiFi access points in indoor environments using non-monotonic signal propagation model. In Control Conference (ASCC), 2013 9th Asian (pp. 1–5).
Wang, J., Urriza, P., Han, Y., & Cabric, D. (2011). Weighted Centroid Localization Algorithm: Theoretical Analysis and Distributed Implementation. IEEE Transactions on Wireless Communications, 10(10), 3403–3413. http://doi.org/10.1109/TWC.2011.081611.102209.
Werner, M. (2014). Indoor Location-Based Services: Prerequisites and Foundations. Springer.
Zhang, Z., Zhou, X., Zhang, W., Zhang, Y., Wang, G., Zhao, B. Y., & Zheng, H. (2011). I am the antenna: accurate outdoor ap location using smartphones. In Proceedings of the 17th annual international conference on Mobile computing and networking (pp. 109–120).
Zhao, F., Luo, H., Geng, H., & Sun, Q. (2014). An RSSI gradient-based AP localization algorithm. China Communications, 11(2), 100–108. http://doi.org/10.1109/CC.2014.6821742.
Acknowledgments
The authors gratefully acknowledge funding from the European Union through the GEO-C project (H2020-MSCA-ITN- 2014, Grant Agreement Number 642332, http://www.geo-ceu/).
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Mendoza-Silva, G.M., Torres-Sospedra, J., Huerta, J., Montoliu, R., Benítez, F., Belmonte, O. (2017). Situation Goodness Method for Weighted Centroid-Based Wi-Fi APs Localization. In: Gartner, G., Huang, H. (eds) Progress in Location-Based Services 2016. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-47289-8_2
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