Localization accuracy of farmland wireless sensor network localization algorithm based on received signal strength indicator

Localization accuracy of farmland wireless sensor network localization algorithm based on received signal strength indicator

Yisheng Miao Huarui Wu  Huaji Zhu  Yuling Song 

National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China

Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China

Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling 712100, China

Corresponding Author Email: 
31 October 2018
| Citation



This paper attempts to improve the localization accuracy under the farmland environment. The accuracy of the localization algorithms based on received signal strength indicator (RSSI) hinges on the working environment. However, there are many disturbances during the wireless signal propagation in farmland wireless sensor network (WSN), such as fading, shielding, reflection and scattering. The impacts of these disturbances vary with the plant growth. Considering these, the author adopted an improved RSSI-based localization method, which divides the target area into multiple small triangles and let each node decides its local triangle. Then, a global path loss exponent was calculated for the entire localization area, and local exponents were also computed for each small triangle. Through example verification, the proposed algorithm was proved to have good localization accuracy and good adaptability to the time-varying environment in farmland. The research findings provide a reference for location estimation in large-scale farmland and real-time channel modeling.


farmland wireless sensor network (WSN), localization methods, received signal strength indicator (RSSI), range based localization, path loss exponent

1. Introduction
2. Network model and assumptions
3. Evaluation of Path Loss Exponent
4. Localization Based on Rssi
5. Experiment and analysis
6. Conclusions

This work was financially supported by Beijing Natural Science Foundation (4172024), Natural Science Foundation of China (61871041, 61571051) and Opening Foundation of Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture (2017AIOT-08).


Adewumi O. G., Djouani K., Kurien A. M. (2013). RSSI based indoor and outdoor distance estimation for localization in WSN. IEEE International Conference on Industrial Technology, Vol. 113, No. 8, pp. 1534-1539. https://doi.org/10.1109/ICIT.2013.6505900

Ahmad N. M., Amin A. H. M., Abdollah M. F., Yusof R. (2015). An empirical investigation of RSSI-based distance estimation for wireless indoor positioning system. International Journal of Wireless & Mobile Computing, Vol. 8, No. 2, pp. 206. https://doi.org/10.1504/IJWMC.2015.068626

Anand P. D., Woo H., Lee C. (2015). A novel range-free localization algorithm based on optimal anchor placement and reliable anchor selection in wireless sensor network. International Journal of Applied Engineering Research, Vol. 10, No. 15, pp. 35264-35271.

Blumrosen G., Hod B., Anker T., Dolev D., Rubinsky B. (2013). Enhancing RSSI-based tracking accuracy in wireless sensor networks. Acm Transactions on Sensor Networks, Vol. 9, No. 3, pp. 1-28. https://doi.org/10.1145/2480730.2480732

Chen S., Qiao X., Mao J., Yu Y. (2015). RSSI-based twice location method for indoor positioning. Chinese Journal of Sensors & Actuators, Vol. 28, No. 4, pp. 572-577. https://doi.org/ 10.3969/j.issn.1004-1699.2015.04.020

Lee W. Y., Hur K., Kim T., Eom D. S., Kim J. O. (2012). Large scale indoor localization system based on wireless sensor networks for ubiquitous computing. Wireless Personal Communications, Vol. 63, No. 1, pp. 241-260. https://doi.org/10.1007/s11277-010-0117-2

Liu X., Zhang S., Bu K. (2016). A locality-based range-free localization algorithm for anisotropic wireless sensor networks. Telecommunication Systems, Vol. 62, No. 1, pp. 3-13. https://doi.org/10.1007/s11235-015-9978-8

Ma Z., Poslad S., Bigham J., Zhang X., Men L. (2017). A BLE RSSI ranking based indoor positioning system for generic smartphones. Wireless Telecommunications Symposium, pp. 1-8. https://doi.org/10.1109/WTS.2017.7943542

Pandey S., Varma S. (2016). A range based localization system in multihop wireless sensor networks: A distributed cooperative approach. Wireless Personal Communications, Vol. 86, No. 2, pp. 615-634. https://doi.org/10.1007/s11277-015-2948-3

Ren Y., Zhong J., Huang J., Song Y., Xin X., Yu N., Feng R. J. (2014). Orthogonal regression based multihop localization algorithm for large-scale underwater wireless sensor networks. International Journal of Distributed Sensor Networks, pp. 1-7. https://doi.org/10.1155/2014/596082

Salari S., Shahbazpanahi S., Ozdemir K. (2013). Mobility-aided wireless sensor network localization via semidefinite programming. IEEE Transactions on Wireless Communications, Vol. 12, No. 12, pp. 5966-5978. https://doi.org/10.1109/TWC.2013.110813.120379

Shang F., Su W., Wang Q., Gao H., Fu Q. (2015). A location estimation algorithm based on RSSI vector similarity degree. International Journal of Distributed Sensor Networks, No. 3, pp. 1-22. https://doi.org/10.1155/2014/371350

Shao H. J., Zhang X. P., Wang Z. (2014). Efficient closed-form algorithms for AOA based self-localization of sensor nodes using auxiliary variables. IEEE Transactions on Signal Processing, Vol. 62, No. 10, pp. 2580-2594. https://doi.org/10.1109/TSP.2014.2314064

Vanheel F., Verhaevert J., Laermans E., Moerman I., Demeester P. (2015). Pseudo-3D RSSI-based WSN localization algorithm using linear regression. Wireless Communications & Mobile Computing, Vol. 15, No. 9, pp. 1342-1354. https://doi.org/10.1002/wcm.2416

Yan X., Song A., Yang Z., Yang W. (2015). An improved multihop-based localization algorithm for wireless sensor network using learning approach. Computers & Electrical Engineering, Vol. 48, No. C, pp. 247-257. https://doi.org/10.1016/j.compeleceng.2015.03.029

Zhang S., Liu X., Wang J., Cao J., Min G. (2015). Accurate range-free localization for anisotropic wireless sensor networks. ACM Transactions on Sensor Networks, Vol. 11, No. 3, pp. 1-25. https://doi.org/10.1145/2746343

Zhao J., Xi W., He Y., Liu Y., Li X. Y., Mo L., Yang Z. (2013). Localization of wireless sensor networks in the wild: Pursuit of ranging quality. IEEE Transactions on Networking, Vol. 21, No. 1, pp. 311-323. https://doi.org/10.1109/TNET.2012.2200906