Skip to main content
Log in

Improving Positioning Algorithm Based on RSSI

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript


Nowadays, a large number of positioning studies based on RSSI technology mainly focused on the coordinate position by measuring the distance using the certain algorithm. The difference between calculated distance and real distance became rather lager due to the poor solution to improve the impact of environment to RSSI, and the bad repeatability. Resulting in the inaccuracy of positioning. According to the RSSI distance measurement technology and Zigbee communication technology, this paper investigated the distance between the unknown node and anchor node based on the “RSSI-Distance”. As the distance was less than 10 m or not, the position can be calculated by the “Mini-Max Positioning Method” or “Maximum Likelihood Estimation Method”, respectively. The results showed that this accuracy of this positioning system can be limited within 3 m.

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.

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

Similar content being viewed by others


  1. Zhou, S. J., Zhang, W. Q., & Luo, J. Q. (2015). Survey of privacy of radio frequency identification technology. Journal of Software,26(4), 960–976.

    Google Scholar 

  2. Liu, M. X., He, Y. G., Deng, F. M., et al. (2015). Design research on wireless humidity sensor node integrated with RFID. Journal of Electronic Measurement and Instrumentation,29(8), 1171–1173.

    Google Scholar 

  3. Zhang, S. G., Liu, G. L., Liu, X., et al. (2014). An energy-efficient and fast missing tag detection algorithm in large scale RFID system. Chinese Journal of Computers,37(2), 434–444.

    Google Scholar 

  4. Gezici, S., Tian, Z., Giannakis, G., et al. (2005). Localization via ultra-wideband radio: a look at positioning aspects for future sensor networks. IEEE Signal Processing Magazine,22(4), 70–84.

    Article  Google Scholar 

  5. Lien, J. (2007). A framework for cooperative localization in ultra-wideband wireless networks. Cambridge: Massachusetts Institute of Technology.

    Google Scholar 

  6. Park, W., & Yoon, M. (2006). The implementation of indoor location system to control ZigBee home network. In Proceedings of IEEE SICE-ICASE. University of Illinois Press, Busan, pp. 2158–2161.

  7. Zhang, X. F., Yu, L. J., Mao, W. W., et al. (2016). The research and application of oxygen intelligent control based on Zigbee in Eriocheir sinensis aquaculture. Journal of Shanghai Ocean University,25(6), 866–872.

    Google Scholar 

  8. Chen, H. L., Wang, Z. B., Wang, Z., et al. (2015). Secure localization scheme against wormhole attack for wireless sensor networks. Journal of Communications,36(3), 2015056-1–2015056-8.

    Google Scholar 

  9. Garg, V., & Jhamb, M. (2013). A review of wireless sensor network on localization techniques. International Journal of Engineering Trends and Technology,4(4), 1049–1053.

    Google Scholar 

  10. He, T., Huang, C. D., Blum, B. M., et al. (2003). Range ~ free localization schemes in large scale sensor networks. In Proceedings of the 9th Annual International Conference Mobile Computing and Networking. ACM Press, San Diego, pp. 81–95.

  11. Zhang, X. R., Xiong, W. L., & Xu, B. G. (2016). Cooperative localization algorithm applying RSSI model in wireless sensor network. Journal of Electronic Measurement and Instrumentation,30(7), 1008–1015.

    Google Scholar 

  12. Yu, P., & Zhan, Y. W. (2016). Moving weighted localization algorithm based on RSSI. Application Research of Computers,33(5), 1450–1452.

    MathSciNet  Google Scholar 

  13. Hou, Q. Z., Shi, B. X., & Liu, Y. F. (2016). On RSSI-based ZigBee location technology. Computer Applications and Software,33(4), 134–137.

    Google Scholar 

  14. Huang, X. (2009). Antenna polarization as complementarities on RSSI-based location identification. In 4th International Symposium on ISWPC2009, pp. 1–5.

  15. Fang, W. H., Xing, Z. Y., Wen, X. J., et al. (2016). Passive acoustic source target positioning method based on smart phone platform TDOA estimation and system implementation. Chinese Journal of Scientific Instrument,37(4), 952–960.

    Google Scholar 

  16. Chen, W. M., Mei, T., Sun, L., Liu, Y. M., et a1. (2008). Error analyzing for RSSI-based localization in wireless sensor networks. In 7th world congress on WCICA2008, pp. 2701–2706.

  17. Zhang, X. R., Xiong, W. L., & Xu, B. G. (2016). A whole process optimization distributed localization strategy based on RSSI in wireless sensor networks. Chinese Journal of Sensors and Actuators,29(12), 1875–1881.

    Google Scholar 

  18. Zhong, L. H., Hu, C. Q., & Jin, J. J. (2014). Analysis and implementation of maximum likelihood estimation positioning algorithm based on RSSI. Journal of Jilin University (Science Edition),52(3), 556–560.

    Google Scholar 

  19. Chengqun, N. G., Jiming, C. H. E. N., & Youxian, S. U. N. (2010). Sensor network localization using kernel spectral regression. Wireless Communications and Mobile Computing,10(8), 1045–1054.

    Google Scholar 

  20. Lu, X., & Peng, Y. (2015). Improved APIT localization algorithm. Computer Engineering and Applications,3, 74–78.

    Google Scholar 

  21. Guo, R., & Ma, Y. F. (2014). The optimization strategy of triangle centroid location algorithm based on RSSI. Microelectronics & Computer,31(3), 111–114.

    Google Scholar 

  22. Wang, W. L., Shi, H., & Li, Y. J. (2015). Weighted centroid localization algorithm based on Mamdani fuzzy theory. Computer Science,42(10), 101–105.

    Article  Google Scholar 

  23. Tang, J., Chen, W., & Chen, S. P. (2015). Indoor adaptive RSSI location algorithm based on the gravitational search algorithm. Information and Control,44(3), 367–371.

    Google Scholar 

  24. He, T., Huang, C. D., Blum, B. M., et al. (2003). Range ~ free localization schemes in large scale sensor networks. In Proceedings of the 9th annual international conference on mobile computing and networking, ACM Press,San Diego, pp. 81 ~ 95.

  25. Bulusu, N., Heidemann, J., & Farin, D. (2000). GPS-less low cost outdoor localization for very small devices. IEEE Personal Communications,10(715), 28–34.

    Article  Google Scholar 

  26. Aspenes, J., Eren, T., Goldenberg, D. K., et al. (2006). A theory of network localization. IEEE Transactions on Mobile Computing,5(12), 1663–1678.

    Article  Google Scholar 

  27. Basagni, S., Carosi, A., Melacnoudis, E., Petrioli, C., & Mng, Z. (2006). Protocols and model for sink mobility in wireless sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review.,10, 28–30.

    Article  Google Scholar 

  28. Long, H. Y., Zhang, T. F., Guo, H., Liang, M. Y., Ding, J., et al. (2016). Research on the CC2530 Based RSSI ranging technology. Electronics World,6, 168–170.

    Google Scholar 

Download references


This paper is supported by the National Natural Science Foundation of China (Grant No. U1504602), China Postdoctoral Science Foundation(Grant No. 2015M572141), Science and Technology Plan Projects of Henan Province (Grant No. 162102310147). Education Department of Henan Province Science and Technology Key Project Funding (Grant No. 14A520065). Research Innovation Foundation of Zhoukou Normal University (zknuA201408) and Introduction of Zhoukou Normal University scientific research grants project (ZKNU2014124). Key Scientific and Technological Research Projects in Henan Province (Grand No. 192102210125). In addition, the authors also will thank the anonymous reviewers for their comments and suggestions.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Shi Dong.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, X., Dong, S. Improving Positioning Algorithm Based on RSSI. Wireless Pers Commun 110, 1947–1961 (2020).

Download citation

  • Published:

  • Issue Date:

  • DOI: