Abstract
To overcome the disadvantages of the location algorithm based on received signal strength indication (RSSI) in the existing wireless sensor networks (WSNs), a novel adaptive cooperative location algorithm is proposed. To tolerate some minor errors in the information of node position, a reference anchor node is employed. On the other hand, Dixon method is used to remove the outliers of RSSI, the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively. Simulations are run to evaluate the performance of the algorithm. The results show that the proposed algorithm offers more precise location and better stability and robustness.
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L. He, Z. Chen, J. D. Xu. Optimizing data collection path in sensor networks with mobile elements. International Journal of Automation and Computing, vol. 8, no. 1, pp. 69–77, 2011.
T. T. Li, T. G. Jia, M. R. Fei, H. S. Hu. Time delay characteristic of industrial wireless networks based on IEEE 802.15.4a. International Journal of Automation and Computing, vol. 8, no. 2, pp. 170–176, 2011.
H. Abusaimeh, S. H. Yang. Balancing the power consumption speed in flat and hierarchical WSN. International Journal of Automation and Computing, vol. 5, no. 4, pp. 366–375, 2008.
J. Z. Lin, X. Zhou, Y. Li. A minimum-energy pathpreserving topology control algorithm for wireless sensor networks. International Journal of Automation and Computing, vol. 6, no. 3, pp. 295–300, 2009.
H. Abusaimeh, S. H. Yang. Dynamic cluster head for lifetime efficiency in WSN. International Journal of Automation and Computing, vol. 6, no. 1, pp. 48–54, 2009.
L. M. Sun, J. Z. Li, Y. Chen, H. S. Zhu. Wireless Sensor Networks, Beijing, China: Tsinghua University Press, pp. 3–4, 2005. (in Chinese)
J. M. Gilbert, F. Balouchi. Comparison of energy harvesting systems for wireless sensor networks. International Journal of Automation and Computing, vol. 5, no. 4, pp. 334–347, 2008.
L. Xue, X. P. Guan, Z. X. Liu, Q. C. Zheng. A powerand coverage-aware clustering scheme for wireless sensor networks. International Journal of Automation and Computing, vol. 7, no. 4, pp. 500–508, 2010.
T. He, C. D. Huang, B. M. Blum, J. A. Stankovic, T. Abdelzaher. Range-free localization schemes for large scale sensor networks. In Proceedings of the 9th Annual International Conference on Mobile Computing and Networking, ACM, San Diego, USA, pp. 81–95, 2003.
N. Wang, X. L. Shen. Research on WSN nodes location technology in coal mine. In Proceedings of International Forum on Computer Science-technology and Applications, IEEE, Chongqing, China, pp. 232–234, 2009.
K. Yu, Y. J. Guo. Statistical NLOS identification based on AOA, TOA, and signal strength. IEEE Transactions on Vehicular Technology, vol. 58, no. 1, pp. 274–286, 2009.
J. D. Li, X. Y. Sun, P. Y. Huang, J. Y. Pang. Performance analysis of active target localization using TDOA and FDOA measurements in WSN. In Proceedings of the 22nd International Conference on Advanced Information Networking and Applications — Workshops, IEEE, Okinawa, Japan, pp. 585–589, 2008.
C. Khauphung, P. Keeratiwintakorn, K. Kaemarungsi. On robustness of centralized-based location determination using WSN. In Proceedings of the 14th Asia-Pacific Conference on Communications, IEEE, Tokyo, Japan, pp. 1–5, 2008.
W. Z. Ren, L. M. Xu, D. J. Zou, Z. L. Deng. Positioning algorithm using maximum likelihood estimation of RSSI difference in wireless sensor networks. Journal of Data Acquisition & Processing, vol. 24, no. 6, pp. 757–761, 2009. (in Chinese)
P. Kumar, L. Reddy, S. Varma. Distance measurement and error estimation scheme for RSSI based localization in wireless sensor networks. In Proceedings of the 5th IEEE Conference on Wireless Communication and Sensor Networks, IEEE, Allahabad, India, pp. 1–4, 2009.
N. Bulusu, J. Heidemann, D. Estrin. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, vol. 7, no. 5, pp. 28–34, 2000.
J. Blumenthal, R. Grossmann, F. Golatowski, D. Timmermann. Weighted centroid localization in Zigbee-based sensor networks. In Proceedings of IEEE International Symposium on Intelligent Signal Processing, IEEE, Alcala de Henares, Spain, pp. 1–6, 2007.
K. Benkič M. Malajner, P. Planinšič, Ž. Čučej. Using RSSI value for distance estimation in wireless sensor networks based on ZigBee. In Proceedings of the 15th International Conference on Systems, Signals and Image Processing, IEEE, Bratislava, Slovakia, pp. 303–306, 2008.
R. Behnke, D. Timmermann. AWCL: Adaptive weighted centroid localization as an efficient improvement of coarse grained localization. In Proceedings of the 5thWorkshop on Positioning, Navigation and Communication, IEEE, Hannover, Germany, pp. 243–250, 2008.
Y. J. Chen, Q. Pan, Y. Liang, Z. T. Hu. AWCL: adaptive weighted centroid target localization algorithm based on RSSI in WSN. In Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology, IEEE, Chengdu, China, pp. 331–336, 2010.
ITU-R Criteria for Propagation data and prediction methods for the planning of indoor radio communication systems and ratio local area networks in the frequency range 900MHz to 100GHz, ITU-R Rec. P. 1238, 1999.
China Criteria for Statistical Interpretation of Datadetection and Treatment of Outliers in the Normal Sample, China’s Standard GB/T 4883-2008, 2008.
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This work was supported by National Natural Science Foundation of China (No.60872038) and Natural Science Foundation of Chongqing (CSTC2009BA2064).
Wen-Jiang Feng received his Ph.D. degree in electrical engineering from Chongqing University, Chongqing, China in 2000. He is currently a supervisor for Ph.D. students at College of Communication Engineering, Chongqing University. He is also a professional assessor of National Science Fund of China and senior member of China Communication Society.
His research interests include broadband wireless access technology, cognitive radio, and signal processing in communications.
Xiao-Wei Bi received his B. Sc. degree in electronic information engineering from Chongqing University, Chongqing, China in 2009. He is currently aM. Sc. student in circuits and systems at College of Communication Engineering, Chongqing University.
His research interests include circuits and systems in communication, tracking telemetering and command, wireless sensor networks.
Rong Jiang received her B. Sc. degree in communication engineering from Chongqing University, Chongqing, China in 2011. She is currently a graduate student of communication and information system at College of Communication Engineering, Chongqing University.
Her research interests include localization and cognitive radio.
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Feng, WJ., Bi, XW. & Jiang, R. A novel adaptive cooperative location algorithm for wireless sensor networks. Int. J. Autom. Comput. 9, 539–544 (2012). https://doi.org/10.1007/s11633-012-0677-6
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DOI: https://doi.org/10.1007/s11633-012-0677-6