Abstract
Various positioning techniques have been widely developed based on received signal strength indicator (RSSI) in Wireless Sensor Network (WSN) positioning systems. Multilateration-based positioning technique is simple and easy to realize, but it can not provide very high positioning accuracy caused by fluctuation of range measurement. Fingerprinting technique is a promising method benefitting from its high precision. However, the process of building radio map cost too much time and labor. In this paper, a fusion algorithm based on both multilateration and fingerprinting is proposed to reduce cost and maintain high accuracy at the same time. An adaptive radio propagation mode is presented in this algorithm as well as a multilateration approaches based on sparse fingerprint. Factor graph is adopted to fuse the results of these two positioning techniques. Simulation experiments demonstrate that the proposed positioning fusion algorithm performs much better than any of the original algorithms participated in the fusion process.
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References
Fang, S.H., Wang, C.H., Huang, T.Y., Yang, C.H.: An enhanced ZigBee indoor positioning system with an ensemble approach. IEEE Commun. Lett. 16(16), 564–567 (2012)
Wang, L., Wong, W.-C.: Fusion of multiple positioning algorithms. In: 2011 8th International Conference on Information, Communications and Signal Processing (ICICS), pp. 1–5. IEEE Press (2011)
Han, G., Jiang, J., Zhang, C., Duong, T., Guizani, M., Karagiannidis, G.: A survey on mobile anchor node assisted localization in wireless sensor networks. IEEE Commun. Surv. Tutor. 18(3), 2220–2243 (2016)
Lee, B., Chung, W.: Multi-target three-dimensional indoor navigation on a PDA in a wireless sensor network. IEEE Sens. J. 11(3), 799–807 (2011)
Subhan, F., Hasbullah, H., Ashraf, K.: Kalman filter-based hybrid indoor position estimation technique in bluetooth networks. Int. J. Navig. Obs. (2013)
Han, S., Gong, Z., Meng, W., Li, C.: Automatic precision control positioning for wireless sensor network. IEEE Sens. J. 16(7), 2140–2150 (2016)
Zhao, W., Meng, W., Chi, Y., Han, S.: Factor graph based multi-source data fusion for wireless localization. In: IEEE Wireless Communications and Networking Conference, Doha, pp. 592–597. IEEE Press (2016)
Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 61401119), the National Science and Technology Major Project (No. 2015ZX03004002-004), the Distinguished Academic Leadership Foundation of Harbin (No. 2014RFXXJ002) and the Science and Technology Project of Ministry of Public Security China (No. 2015GABJC37).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhao, W., Han, S., Meng, W., Gong, Z. (2018). RSSI Based Positioning Fusion Algorithm in Wireless Sensor Network Using Factor Graph. In: Chen, Q., Meng, W., Zhao, L. (eds) Communications and Networking. ChinaCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 210. Springer, Cham. https://doi.org/10.1007/978-3-319-66628-0_55
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DOI: https://doi.org/10.1007/978-3-319-66628-0_55
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