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.
武晓琳, 单志龙, 曹树林, 曹楚裙. 基于接收信号强度指示测距的蒙特卡罗盒移动节点定位算法[J]. 计算机应用, 2015, 35(4): 916-920.
WU Xiaolin, SHAN Zhilong, CAO Shulin, CAO Chuqun. Monte Carlo boxed localization algorithm for mobile nodes based on received signal strength indication ranging. Journal of Computer Applications, 2015, 35(4): 916-920.
[1] ZENG F, SUN Z, LUO J, et al. Improved node localization algorithm for wireless sensor network[J]. Journal on Communications, 2008, 29(11):62-66.(曾凡仔, 孙正章, 罗娟,等. 无线传感器网络的节点定位方法[J].通信学报, 2008, 29(11):62-66.) [2] DANG X, LI X. Weighted correction model in wireless sensor network localization[J]. Journal of Computer Applications, 2012, 32(2): 355-358.(党小超, 李小艳. 无线传感器网络节点定位加权校正模型[J]. 计算机应用, 2012, 32(2): 355-358.) [3] CHEN Y, TING Y, KE C, et al. Efficient localization scheme with ring overlapping by utilizing mobile anchors in wireless sensor networks[J]. ACM Transactions on Embedded Computing Systems, 2013,12(2): Article No. 20. [4] ZHENG Y, WANG H, WAN L, et al. A placement strategy for accurate TOA location algorithm[C]// CNSR 2009: Proceedings of the Seventh Annual Communication Networks and Services Research Conference. Piscataway: IEEE Press, 2009:166-170. [5] ZHANG W, YIN Q, FENG X, et al. Distributed TDoA estimation for wireless sensor networks based on frequency-hopping in multipath environment[C]// Proceedings of the 2010 IEEE 71st Vehicular Technology Conference. Piscataway: IEEE Press, 2010:1-5. [6] SHEN J, HUANG C, LUO H, et al. Localization algorithm of model parameters real-time estimate based on RSSI optimized[J]. Computer Engineering and Design, 2012, 33(2): 464-468.(沈军, 黄春华, 罗护,等. 基于RSSI优化的模型参数实时估计定位算法[J]. 计算机工程与设计, 2012,33 (2):464-468.) [7] AL-JAZZAR S, GHOGHO M,MCLERNON D. A joint TOA/AOA constrained minimization method for locating wireless devices in non-line-of-sight environment[J].IEEE Transactions on Vehicular Technology, 2009, 58(1): 468-472. [8] HU Y, ZHANG H. An improved algorithm for the centroid localization of wireless sensor network [J]. Computer Engineering and Science, 2012, 34(2):45-49.(胡咏梅, 张欢. 一种改进的无线传感器网络质心定位算法[J]. 计算机工程与科学, 2012, 34(2):45-49.) [9] CHENG W, LI J, LI H. An improved APIT location algorithm for wireless sensor networks[C]// Proceedings of the 2012 Advances in Electrical Engineering and Automation, AISC 139. Berlin: Springer-Verlag, 2012: 113-119. [10] 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. [11] 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.) [12] JUANG P, OKI H, WANG Y, et al. Energy-efficient computing for wildlife tracking: Design tradeoffs and early experiences with ZebraNet[C]// Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems. New York: ACM Press, 2002:96-107. [13] HU L, EVANS D. Localization for mobile sensor networks[C]// Proceedings of the 10th International Conference on Mobile Computing and Networking. New York: ACM Press, 2004: 45-57. [14] MEI J, CHEN D, XIN L. Optimized localization scheme for mobile wireless sensor networks based on Monte Carlo method[J]. Chinese Journal of Sensors and Actuators, 2013, 5: 017.(梅举, 陈涤, 辛玲. 基于蒙特卡洛方法的移动传感网节点定位优化算法[J]. 传感技术学报, 2013, 26(5): 689-693.) [15] 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. [16] 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. [17] BAGGIO A, LANGENDOEN K. Monte Carlo localization for mobile wireless sensor networks[J]. Ad Hoc Networks, 2008, 6(5): 718-733.
2015, Vol. 35 
