Abstract
Node localization is an important supporting technology for wireless sensor networks (WSN). Existing range-free localization solutions suffer from low accuracy, while range-based methods achieve good accuracy but costly for ranging hardware. Instead of directly mapping received signal strength indicator (RSSI) values into physical distances, we propose a novel signal-based signature distance (SSD) estimation and localization scheme for WSN. In the proposed scheme, the near-far relationship between nodes is first qualified through comparing of their RSSI, and then a relative map is constructed based on MDS method. Finally, we obtain the node positions through procrustes analysis. In order to verify the effectiveness of the proposed design, we simulate the design in an irregular network with 200 randomly deployed nodes, and develop a prototype system with 25 MICAz motes in real outdoor environments. Results show that our design achieves better positioning performance and observably reduces localization errors.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (Grant No. 51674255), the Natural Science Foundation of Jiangsu Province (Grant No. BK20160274), the Department of Science and Technology Project of Jiangsu Province (Grant No. BY2016026-03), the China Postdoctoral Science Special Foundation (Grant No. 2016T90523).
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Chen, P., Yin, Y., Gao, S., Niu, Q. (2017). SSD: Signal-Based Signature Distance Estimation and Localization for Sensor Networks. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_21
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DOI: https://doi.org/10.1007/978-3-319-60033-8_21
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