Wireless Personal Communications

, Volume 72, Issue 1, pp 461–507 | Cite as

Taxonomy of Fundamental Concepts of Localization in Cyber-Physical and Sensor Networks

  • Anis Koubâa
  • Maissa Ben Jamâa


Localization is a fundamental task in Cyber-Physical Systems (CPS), where data is tightly coupled with the environment and the location where it is generated. The research literature on localization has reached a critical mass, and several surveys have also emerged. This review paper contributes on the state-of-the-art with the proposal of a new and holistic taxonomy of the fundamental concepts of localization in CPS, based on a comprehensive analysis of previous research works and surveys. The main objective is to pave the way towards a deep understanding of the main localization techniques, and unify their descriptions. Furthermore, this review paper provides a complete overview on the most relevant localization and geolocation techniques. Also, we present the most important metrics for measuring the accuracy of localization approaches, which is meant to be the gap between the real location and its estimate. Finally, we present open issues and research challenges pertaining to localization. We believe that this review paper will represent an important and complete reference of localization techniques in CPS for researchers and practitioners and will provide them with an added value as compared to previous surveys.


Fundamental techniques of localization Localization accuracy metrics Localization real-world challenges Localization open issues 



This work is funded by the R-Track project [72] under the grant 8-INF-2008 of the National Plan for Sciences and Technology (NPST), managed by the Science and Technology Unit of Al-Imam Mohamed bin Saud University and by King AbdulAziz Center for Science and Technology (KACST).


  1. 1.
    Ali-Loytty, S., Perala, T., Honkavirta, V., & Piche, R. (2009). Fingerprint kalman filter in indoor positioning applications. In Control applications, (CCA) intelligent control (ISIC) (pp. 1678–1683). doi: 10.1109/CCA.2009.5281069.
  2. 2.
    Amundson, I., & Koutsoukos, X. D. (2009). A survey on localization for mobile wireless sensor networks. In Proceedings of the 2nd international conference on mobile entity localization and tracking in GPS-less environments, MELT’09 (pp. 235–254). Berlin: Springer.
  3. 3.
    Baccour, N., Koubâa, A., Youssef, H., Jamâa, M. B., do Rosário, D., Alves, M., & Becker, L. B. (2010). F-lqe: A fuzzy link quality estimator for wireless sensor networks. In EWSN (pp. 240–255).Google Scholar
  4. 4.
    Bahl, P., & Padmanabhan, V. N. (2000). Radar: An in-building rf-based user location and tracking system. In INFOCOM(pp. 775–784).Google Scholar
  5. 5.
    Barsocchi, P., Lenzi, S., Chessa, S., & Giunta, G. (2009). Virtual calibration for rssi-based indoor localization with ieee 802.15.4. In IEEE international conference on communications (2009). ICC ’09 (pp. 1–5). doi: 10.1109/ICC.2009.5199566.
  6. 6.
    Ben Jamâa, M., Kouba, A., & Kayani, Y. (2012). Easyloc: RSS-Based localization made easy. Procedia Comput Sci., 10, 1127–1133.
  7. 7.
    Bernardos, A. M., Casar, J. R., & Tarrıo, P. (2010). Real time calibration for rss indoor positioning systems. East (September), 15–17.Google Scholar
  8. 8.
    Blumenthal, J., Grossmann, R., Golatowski, F., & Timmermann, D. (2007). Weighted centroid localization in zigbee-based sensor networks. In IEEE international symposium on intelligent signal processing (WISP 2007) (pp. 1–6). doi: 10.1109/WISP.2007.4447528.
  9. 9.
    Bolliger, P. (2008). 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, MELT ’08 (pp. 55–60). New York, NY: ACM. doi: 10.1145/1410012.1410025.
  10. 10.
    Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2007). Localization systems for wireless sensor networks. IEEE Magazine of Wireless Communications, 14(6), 6–12. doi: 10.1109/MWC.2007.4407221.CrossRefGoogle Scholar
  11. 11.
    Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine, 7(5), 28–34.Google Scholar
  12. 12.
    Chen, Y., Kleisouris, K., Li, X., Trappe, W., & Martin, R. P. (2006). The robustness of localization algorithms to signal strength attacks: A comparative study. In DCOSS’06 (pp. 546–563).Google Scholar
  13. 13.
    Chen, Y., Trappe, W., & Martin, R. P. (2007). Detecting and localizing wireless spoofing attacks. In SECON’07 (pp. 193–202).Google Scholar
  14. 14.
    Chintalapudi, K., Padmanabha Iyer, A., & Padmanabhan, V. N. (2010). Indoor localization without the pain. In Proceedings of the sixteenth annual international conference on Mobile computing and networking, MobiCom ’10 (pp. 173–184). New York, NY: ACM.Google Scholar
  15. 15.
    Chrysikos, T., & Kotsopoulos, S. (2009). Impact of channel-dependent variation of path loss exponent on wireless information-theoretic security. In Proceedings of the 2009 conference on Wireless telecommunications symposium, WTS’09 (pp. 384–390). Piscataway, NJ: IEEE Press.
  16. 16.
  17. 17.
    Costa, J. A., & Patwari, N. (2006). Distributed weighted-multidimensional scaling for node localization in sensor networks. ACM Transaction on Sensor Networks, 2(1), 39–64. doi: 10.1145/1138127.1138129.CrossRefGoogle Scholar
  18. 18.
    Do, K. (2008). Effect of an additional sensor on aoa localization performance. Simulation, 11(2), 1–5.Google Scholar
  19. 19.
    Drane, C., Macnaughtan, M., & Scott, C. (1998). Positioning gsm telephones. IEEE Communications Magazine, 36(4), 46–54.CrossRefGoogle Scholar
  20. 20.
    Efrat, A., Forrester, D., Iyer, A., Kobourov, S. G., Erten, C., & Kilic, O. (2010). Force-directed approaches to sensor localization. ACM Transactions on Sensor Networks, 7, 271–2725. doi: 10.1145/1807048.1807057.CrossRefGoogle Scholar
  21. 21.
    Elnahraway, E., Li, X., & Martin, R. P. (2004). The limits of localization using rss. In Proceedings of the 2nd international conference on embedded networked sensor systems, SenSys ’04 (pp. 283–284). New York, NY: ACM. doi: 10.1145/1031495.1031537.
  22. 22.
    Erol-Kantarci, M., Mouftah, H. T., & Oktug, S. (2011). A survey of architectures and localization techniques for underwater acoustic sensor networks. IEEE Communications Surveys & Tutorials, 1–16. doi: 10.1109/SURV.2011.020211.00035.
  23. 23.
    Esposito, C., Cotroneo, D., & Ficco, M. (2009). Calibrating rss-based indoor positioning systems. In Proceedings of the 2009 IEEE international conference on wireless and mobile computing, networking and communications, WIMOB ’09 (pp. 1–6). Washington, DC: IEEE Computer Society. doi: 10.1109/WiMob.2009.11.
  24. 24.
    Figueiras, J., & Frattasi, S. (2010). Mobile positioning and tracking: From conventional to cooperative techniques. London: Wiley.
  25. 25.
    Goldoni, E., Savioli, A., Risi, M., & Gamba, P. (2010). Experimental analysis of RSSI-based indoor localization with IEEE 802.15.4 (pp. 71–77). doi: 10.1109/EW.2010.5483396.
  26. 26.
    Gotsman, C., & Koren, Y. (2004). Distributed graph layout for sensor networks. In J. Pach (Ed.), Graph drawing, lecture notes in computer science (Vol. 3383, pp. 273–284). Berlin: Springer.Google Scholar
  27. 27.
    Gu, Y., Lo, A., & Niemegeers, I. G. (2009). A survey of indoor positioning systems for wireless personal networks. IEEE Communications Surveys & Tutorials, 11(1), 13–32.Google Scholar
  28. 28.
    Guvenc, I., & Chong, C. C. (2009). A survey on toa based wireless localization and nlos mitigation techniques. IEEE Communications Surveys & Tutorials, 11, 107–124. doi: 10.1109/SURV.2009.090308.CrossRefGoogle Scholar
  29. 29.
    Harter, A., Hopper, A., Steggles, P., Ward, A., & Webster, P. (1999). The anatomy of a context-aware application. In Proceedings of the 5th annual ACM/IEEE international conference on mobile computing and networking, MobiCom ’99 (pp. 59–68). New York, NY: ACM. doi: 10.1145/313451.313476.
  30. 30.
    He, T., Huang, C., John, B. M. B., & Stankovic Abdelzaher, T. (2003). Range-free localization schemes for large scale sensor, networks. doi: 10.1145/938985.938995.
  31. 31.
    Ho, K., & Chan, Y. (1993). Solution and performance analysis of geolocation by tdoa. IEEE Transactions on Aerospace and Electronic Systems, 29(4), 1311–1322. doi: 10.1109/7.259534.CrossRefGoogle Scholar
  32. 32.
    Honkavirta, V., Perala, T., Ali-Loytty, S., & Piche, R. (2009). A comparative survey of wlan location fingerprinting methods. In The 6th workshop on positioning, navigation and. Communication (pp. 243–251). doi: 10.1109/WPNC.2009.4907834.
  33. 33.
    Jamâa, M. B., & Koubâa, A. (2012). Demo abstract: Rss-based localization in sensor networks does not need pre-deployment profiling. In The 9th European conference on wireless sensor networks (EWSN).Google Scholar
  34. 34.
    Jasch, A., Feuerle, T., Scoor, G., & Hecker, P. (2010). Geometrical siting considerations for wide area multilateration systems (pp. 1304–1308). doi: 10.1109/PLANS.2010.5507349.
  35. 35.
    Ji, X., & Zha, H. (2004). Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling. In Proceedings of IEEE INFOCOM, Hong Kong, China (pp. 2652–2661).Google Scholar
  36. 36.
    Jiao, L., Xing, J., & Li, F. Y. (2009). Performance comparison of residual related algorithms for toa positioning in wireless terrestrial and sensor networks. In First international conference on wireless communication, vehicular technology, information theory and aerospace and electronic systems technology, 2009. Wireless VITAE (pp. 278–283). doi: 10.1109/WIRELESSVITAE.2009.5172462.
  37. 37.
    Kaemarungsi, K., & Krishnamurthy, P. (2004). Modeling of indoor positioning systems based on location fingerprinting. In INFOCOM.Google Scholar
  38. 38.
    Kaltiokallio, O., Bocca, M., & Patwari, N. (2012). Follow grandma: Long-term device-free localization for residential monitoring. In Proceedings of the seventh IEEE international workshop on practical issues in building sensor networks applications, SenseApp 2012.Google Scholar
  39. 39.
    Karl, H., & Willig, A. (2005). Protocols and architectures for wireless sensor networks. London: Wiley.CrossRefGoogle Scholar
  40. 40.
    Kleinrock, L., & Silvester, J. (1978). Optimum transmission radii for packet radio networks or why six is a magic number. In IEEE national telecommunications conference (pp. 431–435).Google Scholar
  41. 41.
    Kushki, A., Plataniotis, K. N., & Venetsanopoulos, A. N. (2007). Kernel-based positioning in wireless local area networks. IEEE Transcations on Mobile Computing, 6(6), 689–705.CrossRefGoogle Scholar
  42. 42.
    Langendoen, K., & Reijers, N. (2003). Distributed localization in wireless sensor networks: A quantitative comparison. Computer Networks, 43, 499–518. doi: 10.1016/S1389-1286(03)00356-6.
  43. 43.
    Lazos, L., & Poovendran, R. (2005). Serloc: Robust localization for wireless sensor networks. ACM Transcations Sensor Networks, 1, 73–100. doi: 10.1145/1077391.1077395.CrossRefGoogle Scholar
  44. 44.
    Lederer, S., Wang, Y., & Gao, J. (2009). Connectivity-based localization of large-scale sensor networks with complex shape. ACM Transcations Sensor Networks, 5(4), 1–32.CrossRefGoogle Scholar
  45. 45.
    Li, L., & Kunz, T. (2009). Cooperative node localization using nonlinear data projection. ACM Transcations Sensor Networks, 5(1), 1–26.CrossRefGoogle Scholar
  46. 46.
    Li, M., & Liu, Y. (2007). Rendered path: Range-free localization in anisotropic sensor networks with holes. In Proceedings of the 13th annual ACM international conference on mobile computing and networking, MobiCom ’07 (pp. 51–62). New York, NY: ACM.Google Scholar
  47. 47.
    Li, X. (2009). Ratio-based zero-profiling indoor localization. In IEEE 6th international conference on mobile adhoc and sensor systems, 2009. MASS ’09 (pp. 40–49). doi: 10.1109/MOBHOC.2009.5336964.
  48. 48.
    Li, X. (2009). Ratio-based zero-profiling indoor localization (pp. 40–49). In MASS.Google Scholar
  49. 49.
    Lim, H., Kung, L. C., Hou, J. C., & Luo, H. (2006). Zero-configuration, robust indoor localization: Theory and experimentation. In INFOCOM.Google Scholar
  50. 50.
    Lim, H., Kung, L. C., Hou, J. C., & Luo, H. (2010). Zero-configuration indoor localization over ieee 802.11 wireless infrastructure. Wireless Networks, 16, 405–420. doi: 10.1007/s11276-008-0140-3.CrossRefGoogle Scholar
  51. 51.
    Liu, H., Darabi, H., Banerjee, P., & Liu, J. (2007). Survey of wireless indoor positioning techniques and systems. IEEE Transaction on Systems, MAN, AND Cybernetics Part C Applications and Reviews, 37(6), 1067–1080.CrossRefGoogle Scholar
  52. 52.
    Liu, N., Xu, Z., & Sadler, B. (2008). Low-complexity hyperbolic source localization with a linear sensor array. IEEE Signal Processing Letters, 15, 865–868.Google Scholar
  53. 53.
    Liu, X., Zhang, C., & Hu, J. (2008). Adaptive weights weighted centroid localization algorithm for wireless sensor networks. In 4th international conference on wireless communications, networking and mobile computing (WiCOM ’08) (pp. 1–4). doi: 10.1109/WiCom.2008.851.
  54. 54.
    Mahalik, N. P. (2006). Sensor networks and configuration: Fundamentals, standards, platforms, and applications. Secaucus, NJ: Springer.Google Scholar
  55. 55.
    Mao, G., Anderson, B. D. O., & Fidan, B. (2007). Path loss exponent estimation for wireless sensor network localization. Computer Networks, 51(10), 2467–2483. doi: 10.1016/j.comnet.2006.11.007.zbMATHCrossRefGoogle Scholar
  56. 56.
    Mao, G., Fidan, B., & Anderson, B. D. O. (2007). Wireless sensor network localization techniques. Computer Networks, 51, 2529–2553. doi: 10.1016/j.comnet.2006.11.018.
  57. 57.
    Mao, G., Fidan, B., Mao, G., & Fidan, B. (2009). Localization algorithms and strategies for wireless sensor networks. Hershey, PA: Information Science Reference-Imprint of: IGI Publishing.Google Scholar
  58. 58.
    McCrady, D., Doyle, L., Forstrom, H., Dempsey, T., & Martorana, M. (2000). Mobile ranging using low-accuracy clocks. IEEE Transactions on Microwave Theory and Techniques, 48(6), 951–958. doi: 10.1109/22.846721.CrossRefGoogle Scholar
  59. 59.
    Nagpal, R., Shrobe, H., & Bachrach, J. (2003). Organizing a global coordinate system from local information on an ad hoc sensor network. In IPSN’03: Proceedings of the 2nd international conference on Information processing in sensor networks.Google Scholar
  60. 60.
    Niculescu, D., & Badrinath, B. R. (2003). Ad hoc positioning system (aps) using aoa. In INFOCOM.Google Scholar
  61. 61.
    Official US government information about the global positioning system (gps) and related topics.
  62. 62.
    Paul, A. S., & Wan, E. A. (2009). RSSI-based indoor localization and tracking using sigma-point kalman smoothers. Journal of Selected Topics in Signal Processing, 3(5), 860–873.CrossRefGoogle Scholar
  63. 63.
    Pi-Chun, C. (1999). A non-line-of-sight error mitigation algorithm in location estimation. In Proceedings of the IEEE wireless communications and networking conference, WCNC (pp. 59–68). doi: 10.1109/WCNC.1999.797838.
  64. 64.
    Priyantha, N. B. (2005). The cricket indoor location system. Ph.D. thesis, Cambridge, MA, Adviser-Balakrishnan, Hari.Google Scholar
  65. 65.
    Priyantha, N. B., Balakrishnan, H., Demaine, E. D., & Teller, S. J. (2003). Anchor-free distributed localization in sensor networks. In SenSys (pp. 340–341).Google Scholar
  66. 66.
    Priyantha, N. B., Chakraborty, A., & Balakrishnan, H. (2000). The cricket location-support system. In MobiCom ’00: Proceedings of the 6th annual international conference on Mobile computing and networking (pp. 32–43). New York, NY: ACM. doi: 10.1145/345910.345917.
  67. 67.
    Rabbat, M., & Nowak, R. (2004). Distributed optimization in sensor networks. In IPSN ’04: Proceedings of the 3rd international symposium on information processing in sensor networks (pp. 20–27). New York, NY: ACM. doi: 10.1145/984622.984626.
  68. 68.
    Reichenbach, F., & Timmermann, D. (2006). Indoor localization with low complexity in wireless sensor networks. In IEEE international conference on industrial informatics (pp. 1018–1023). doi: 10.1109/INDIN.2006.275737.
  69. 69.
    Ren, Y., Chuah, M. C., Yang, J., & Chen, Y. (2010). Detecting wormhole attacks in delay-tolerant networks. Wireless Communications, 17, 36–42.
  70. 70.
    Römer, K. (2003). The lighthouse location system for smart dust. In Proceedings of the 1st international conference on mobile systems, applications and services, MobiSys ’03 (pp. 15–30). ACM: New York, NY. doi: 10.1145/1066116.1189036.
  71. 71.
    Rong, P., & Sichitiu, M. (2006). Angle of arrival localization for wireless sensor networks. In 3rd Annual IEEE communications society on sensor and ad hoc communications and networks, 2006. SECON ’06 (Vol. 1 pp. 374–382). doi: 10.1109/SAHCN.2006.288442.
  72. 72.
    Rtrack project.
  73. 73.
    Shang, Y., Ruml, W., Zhang, Y., & Fromherz, M. P. J. (2003). Localization from mere connectivity. In MobiHoc ’03: Proceedings of the 4th ACM international symposium on mobile ad hoc networking & computing (pp. 201–212). New York, NY: ACM. doi: 10.1145/778415.778439.
  74. 74.
    Sources of errors in gps. (1999).
  75. 75.
    Stoleru, R., He, T., & Stankovic, J. A. (2004). Walking gps: A practical solution for localization in manually deployed wireless sensor networks. In Annual IEEE conference on local computer networks (pp. 480–489). doi: 10.1109/LCN.2004.136.
  76. 76.
    Stoleru, R., He, T., & Stankovic, J. A. (2007). Range-free localization. In Chapter in secure localization and time synchronization for wireless sensor and ad hoc networks, Vol. 30.Google Scholar
  77. 77.
    Tateishi, K., & Ikegami, T. (2008). Estimation method of attenuation constant during localization in rssi. In International symposium on communications and information technologies, ISCIT 2008 (pp. 482–487). doi: 10.1109/ISCIT.2008.4700239.
  78. 78.
    Torrieri, D. (1984). Statistical theory of passive location systems. IEEE Transactions on Aerospace and Electronic Systems, 20(2), 183–198. doi: 10.1109/TAES.1984.310439.CrossRefGoogle Scholar
  79. 79.
    Varshavsky, A., Pankratov, D., Krumm, J., & Lara, E. (2008). Calibree: Calibration-free localization using relative distance estimations. In Proceedings of the 6th international conference on pervasive computing, pervasive ’08 (pp. 146–161). Berlin: Springer.Google Scholar
  80. 80.
    Vidal, J., Najar, M., & Jativa, R. (2002). High resolution time-of-arrival detection for wireless positioning systems. In Vehicular technology conference, 2002. Proceedings. VTC 2002-Fall. 2002 IEEE 56th, Vol. 4 (pp. 2283–2287). doi: 10.1109/VETECF.2002.1040627.
  81. 81.
    Wilson, J., & Patwari, N. (2010). Radio tomographic imaging with wireless networks. IEEE Transactions on Mobile Computing, 9(5), 621–632.CrossRefGoogle Scholar
  82. 82.
    Wymeersch, H., Lien, J., & Win, M. Z. (2009). Cooperative localization in wireless networks. In Proceedings of the IEEE (Vol. 97, pp. 427–450).Google Scholar
  83. 83.
    Yeh, L. W., Hsu, M. S., Lee, Y. F., & Tseng, Y. C. (2009). Indoor localization: Automatically constructing today’s radio map by irobot and rfids. In Sensors, 2009 IEEE (pp. 1463–1466). doi: 10.1109/ICSENS.2009.5398451.
  84. 84.
    Zhang, J., Yan, T., Stankovi, J. A., & Son, S. H. (2007). Thunder: Towards practical, zero cost acoustic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Computing and Communications Review, 11, 15–28. doi: 10.1145/1234822.1234827.CrossRefGoogle Scholar
  85. 85.
    Zhong, Z. (2010). Phd dissertation: Range-free localization and tracking in wireless sensor networks.
  86. 86.
    Zhu, J. (1992). Calculation of geometric dilution of precision. IEEE Transactions on Aerospace and Electronic Systems, 28, 893–895.CrossRefGoogle Scholar
  87. 87.
    Zhu, Y., Huang, D., & Jiang, A. (2008). Network localization using angle of arrival. In IEEE international conference on electro/information technology (pp. 205–210). doi: 10.1109/EIT.2008.4554297.
  88. 88.
    Zorzi, F., & Zanella, A. (2009). Opportunistic localization: Modeling and analysis. In VTC spring. IEEE.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.COINS Research GroupPrince Sultan UniversityRiyadhSaudi Arabia
  2. 2.CISTER Research UnitPolytechnic Institute of Porto (ISEP/IPP)PortoPortugal
  3. 3.ReDCAD Research UnitNational School of Engineers of SfaxSfaxTunisia

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