Wireless Networks

, Volume 21, Issue 8, pp 2561–2569 | Cite as

An RSSI-based localization algorithm for outliers suppression in wireless sensor networks

  • Rencheng Jin
  • Zhiping CheEmail author
  • Hao Xu
  • Zhen Wang
  • Liding Wang


Node localization technology is one of the most important technologies in wireless sensor networks. Due to the advantages of saving and convenience, received signal strength indication (RSSI) technology is widely taken to measure the distance between the sensor nodes, and then trilateral localization algorithm which is one of the classic algorithms can calculate the position result quickly. However, the result always comes with an irregularly wide error. Environment, temperature and electromagnetism are generally considered the interference factors, which have been widely researched. From another angle, this study focuses on the error of the algorithm itself, and discusses the stability of equations. A trilateral localization algorithm for outliers suppression is proposed. Through a large number of simulation, it is demonstrated that the proposed algorithm has a good performance than classic trilateral algorithm based-on the nearest three anchor nodes. A significant meaning of this research is that the deepest source of gross errors has been found when we use classic trilateral algorithm.


Localization algorithm Trilateral algorithm Outliers suppression RSSI WSNs 



The authors would like to thank all members of their team and the reviewers who have contributed to improving the quality of this paper. This work was supported in part by the National Basic Research Program of China (973 Program) and National Science and Technology Support Program.


  1. 1.
    Gracioli, G., Frohlich, A. A., Pires, R. P., & Wanner, L. (2011). Evaluation of an RSSI-based location algorithm for wireless sensor networks. Latin America Transactions, IEEE (Revista IEEE America Latina), 9(1), 830–835.CrossRefGoogle Scholar
  2. 2.
    Jang, S.-W., Cho, S.-Y., & Lee, G.-S. (2014). An intelligent guardrail context-awareness system based on acceleration sensors in ubiquitous sensor networks. International Journal of Distributed Sensor Networks, 2014, 1–10.Google Scholar
  3. 3.
    Longkang, W., Baisheng, N., Ruming, Z., Shengrui, Z., & Hailong, L. (2011). ZigBee-based positioning system for coal miners. Procedia Engineering, 26, 2406–2414.CrossRefGoogle Scholar
  4. 4.
    Medina, C., Segura, J. C., & de la Torre, A. (2013). Accurate time synchronization of ultrasonic TOF measurements in IEEE 802.15.4 based wireless sensor networks. Ad Hoc Networks, 11(1), 442–452.CrossRefGoogle Scholar
  5. 5.
    Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and challenges of wireless sensor networks in smart grid. IEEE Transactions on Industrial Electronics, 57(10), 3557–3564.CrossRefGoogle Scholar
  6. 6.
    Cheng, G. (2012). Accurate TOA-based UWB localization system in coal mine based on WSN. Physics Procedia, 24, 534–540.CrossRefGoogle Scholar
  7. 7.
    Wei, Meng, Lihua, Xie, & Wendong, Xiao. (2013). Decentralized TDOA sensor pairing in multihop wireless sensor networks. IEEE Signal Processing Letters, 20(2), 181–184.CrossRefGoogle Scholar
  8. 8.
    Dakkak, M., Nakib, A., Daachi, B., Siarry, P., & Lemoine, J. (2011). Indoor localization method based on RTT and AOA using coordinates clustering. Computer Networks, 55(8), 1794–1803.CrossRefGoogle Scholar
  9. 9.
    Blumrosen, G., Hod, B., Anker, T., Dolev, D., & Rubinsky, B. (2013). Enhanced calibration technique for RSSI-based ranging in body area networks. Ad Hoc Networks, 11(1), 555–569.CrossRefGoogle Scholar
  10. 10.
    Cho, H. H., Lee, R. H., & Park, J. G. (2011). Adaptive parameter estimation method for wireless localization using RSSI measurements. Journal of Electrical Engineering & Technology, 6(6), 883–887.CrossRefGoogle Scholar
  11. 11.
    Zhang, C., Zhou, X., Gao, C., & Wang, C. (2008). On improving the precision of localization with gross error removal. In 28th international conference on distributed computing systems workshops, 2008 . ICDCS’08 (pp. 144–149). IEEE.Google Scholar
  12. 12.
    Chen, Y. C., Sun, W. C., & Juang, J. C. (2010). Outlier detection technique for RSS-based localization problems in wireless sensor networks. In Proceedings of SICE annual conference, 2010 (pp. 657–662). IEEE.Google Scholar
  13. 13.
    Ahn, H. S., & Yu, W. (2009). Environmental-adaptive RSSI-based indoor localization. IEEE Transactions on Automation Science and Engineering, 6(4), 626–633.CrossRefGoogle Scholar
  14. 14.
    Paul, A. S., & Wan, E. A. (2009). RSSI-based indoor localization and tracking using sigma-point kalman smoothers. IEEE Journal of Selected Topics in Signal Processing, 3(5), 860–873.CrossRefGoogle Scholar
  15. 15.
    Wang, L., Wang, X., & Du, X. (2010). Some issues on WSN localization based on MLE. In 8th world congress on intelligent control and automation (WCICA), 2010 (pp. 796–800). IEEE.Google Scholar
  16. 16.
    Wang, X., Yuan, S., Laur, R., & Lang, W. (2011). Dynamic localization based on spatial reasoning with RSSI in wireless sensor networks for transport logistics. Sensors and Actuators A-Physical, 171(2), 421–428.CrossRefGoogle Scholar
  17. 17.
    Rencheng, J., Bo, P., Lisha, M., & Teng, G. (2009). Research on localization method based on RSSI ranging-error compensation. In 5th international conference on wireless communications, networking and mobile computing, 2009 . WiCom’09 (pp. 1–3). IEEE.Google Scholar
  18. 18.
    Lu, G., Krishnamachari, B., & Raghavendra, C. S. (2004). Performance evaluation of the IEEE 802.15.4 MAC for low-rate low-power wireless networks. In IEEE international conference on performance, computing, and communications, 2004 (pp. 701–706). IEEE.Google Scholar
  19. 19.
    Mao, G. Q., Baris, F., & Brian, D. A. (2007). Wireless sensor network localization techniques. Computer Networks, 51, 2529–2553.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Rencheng Jin
    • 1
  • Zhiping Che
    • 1
    Email author
  • Hao Xu
    • 1
  • Zhen Wang
    • 1
  • Liding Wang
    • 1
  1. 1.Research Center of Microsystems TechnologyDalian University of TechnologyDalianPeople’s Republic of China

Personalised recommendations