To solve the shortcomings of sampling efficiency and positioning accuracy of the Monte Carlo localization algorithm in Wireless Sensor Networks (WSN), a Monte Carlo localization Boxed (MCB) algorithm for mobile nodes based on Received Signal Strength Indication (RSSI) ranging was proposed. To improve the positioning accuracy, the filter conditions was strengthened by mapping the ranging information into different distance intervals. At the same time, the samples which had already met the filter conditions were used to create more effective samples so as to improve the sampling efficiency. Finally, the Newton interpolation was used to predict the nodes' trajectory. The closer the trajectory between the sample and the node is, the greater the weight of the sample is, and the best estimate position could be obtained with these weighted samples. The simulation results indicate that the proposed algorithm has good performance in different density of anchor node, communication radius, and movement velocity etc., and compared with the MCB algorithm, the proposed algorithm has higher positioning accuracy.
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YI S, RUML W, ZHANG Y, et al. Localization from mere connectivity [C]// Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York: ACM Press, 2003: 201-212.
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LIU W, WANG E, CHEN Z. Improved DV-Hop localization algorithm in wireless sensor networks [J]. Journal of Chinese Computer Systems, 2011,32(6):1071-1074.(刘文远, 王恩爽, 陈子军. 无线传感器网络中DV-Hop定位算法的改进[J]. 小型微型计算机系统, 2011, 32(6):1071-1074.)
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STEVENS N, VIVEKANANDAN E, WONG V. Dual and mixture Monte Carlo localization algorithms for mobile wireless sensor networks [C]// Proceedings of the 2007 IEEE Wireless Communications and Networking Conference. Piscataway: IEEE Press, 2007:4024-4028.
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YI J, YANG S, CHA H. Multi-hop-based Monte Carlo localization for mobile sensor networks[C]// Proceedings of the Fourth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks. Piscataway: IEEE Press, 2007:162-171.
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BAGGIO A, LANGENDOEN K. Monte Carlo localization for mobile wireless sensor networks[J]. Ad Hoc Networks, 2008, 6(5): 718-733.
2015, Vol. 35 
