基于参考点序列的无线传感器网络节点定位算法

吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (02): 489-493.

基于参考点序列的无线传感器网络节点定位算法

刘影^1,2, 钱志鸿¹, 孙大洋¹

1. 吉林大学通信工程学院, 长春 130022;
2. 辽宁工程技术大学电子与信息工程学院, 辽宁葫芦岛 125105

收稿日期:2011-02-01 出版日期:2012-03-01 发布日期:2012-03-01
通讯作者: 钱志鸿(1957-),男,教授.研究方向:无线网络通信系统的信号分析和处理,通信系统微弱信号检测理论与应用.E-mail:dr.qzh@163.com E-mail:dr.qzh@163.com
作者简介:刘影(1983-),女.研究方向:无线传感器网络.E-mail:lycommunication@126.com
基金资助:
国家自然科学基金项目(60940010,61071073);高等学校博士学科点专项科研基金项目(20090061110043).

Node localization scheme for wireless sensor networks based on reference node sequence

LIU Ying^1,2, QIAN Zhi-hong¹, SUN Da-yang¹

1. College of Communication Engineering, Jilin University, Changchun 130022, China;
2. School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China

Received:2011-02-01 Online:2012-03-01 Published:2012-03-01

摘要/Abstract

摘要： 提出了一种基于参考点序列(Reference node sequence,RNS)的无线传感器网络定位算法,该算法对定位空间的锚节点建立voronoi多边形,以此生成由锚节点组成的voronoi图,并将voronoi图的顶点记为参考点,为定位空间增加了若干锚节点信息。从而使与传感器节点通信的锚节点数目增加,改善了锚节点不足给定位带来的负面影响。其次建立参考点和锚节点到传感器节点的序列等级,根据序列等级估计出传感器节点的位置。仿真结果表明,与DV-Hop算法和质心算法相比,本文算法可以更准确地估计出节点的位置,提高定位精度。

关键词: 信息处理技术, 无线传感器网络, 网络节点定位, voronoi图, 参考点序列, 序列等级

Abstract: A node localization algorithm based on reference node sequence is proposed to improve the location accuracy for wireless sensor networks. The algorithm builds the voronoi polygon using the anchor nodes in the localization space, then to generate the voronoi graph. The vertices of the voronoi graph are used as the reference nodes, namely virtual anchor nodes, which increase the anchor node information in the localization space. Therefore, the number of anchor nodes, which can communicate with sensor nodes, increases. In such way, the sensor nodes have more information to determine their space position to over come the negative effect in localization due to the inadequate number of anchor nodes. The proposed scheme builds the sequence rank of the virtual nodes and anchor nodes to the sensor nodes; and according to the sequence rank to estimate the spatial location of the sensor nodes. Simulation results demonstrate that the proposed algorithm can efficiently estimate nodes location and greatly improves the localization accuracy.

Key words: information processing, wireless sensor network, network nodes localization, voronoi polygon, reference nodes sequence, sequence rank

中图分类号:

TN92

刘影, 钱志鸿, 孙大洋. 基于参考点序列的无线传感器网络节点定位算法[J]. 吉林大学学报(工学版), 2012, 42(02): 489-493.

LIU Ying, QIAN Zhi-hong, SUN Da-yang. Node localization scheme for wireless sensor networks based on reference node sequence[J]. 吉林大学学报(工学版), 2012, 42(02): 489-493.

参考文献

[1] Martusevicius V, Kazanavicius E.Self-localization system for wireless sensor network［J］.Elektronika Ir Elektrothchnika, 2010, 16(10): 17-20.

[2] Lin C, Xiong N, Park J H, et al.Dynamic power management in new architecture of wireless sensor networks［J］.International Journal of Communication Systems, 2009, 22(6):671-693.

[3] Laurendeau C, Barbeau M. Centroid localization of uncooperative nodes in wireless sensor networks using a relative span weighting methord［J］.EURASIP Journal on Wireless Communications and Networking-special Issue on Wireless Network Algorithms, Systems and Applications, 2010:1-10.

[4] Nicolescu D, Nath B. Ad-Hoc positioning system (APS)//IEEE Global Telecommunications Conference, 2001, 5:2926-2931.

[5] Franceso Chiti, Laura Pierucci. APIT:a bit of improvement for applications in critical scenarios//6th International Wireless Communications and Mobile Computing Conference, Caen France, 2010,2010(Suppl):794-798.

[6] Kiran Yedavalli, Bhaskar Krishnamachari. Sequence-based localization in wireless sensor networks［J］.IEEE Transactions on Mobile Computing, 2008, 7(1):81-94.

[7] Blumenthal Jan, Grossmann Ralf, Golatowski Frank, et al.Weighted centroid localization in Zigbee-based sensor network［J］. In IEEE International Symposium on Intelligent Signal Processing, Madrid, 2007:1-6.

[8] 刘峰,张翰,杨骥.一种基于加权处理的无线传感器网络平均跳距离估计算法［J］.电子与信息学报, 2008,30(5): 1222-1225. Liu Feng,Zhang Han, Yang Ji.An average one-hop distance estimation algorithm based on weighted disposal in wireless sensor network［J］.Journal of Electronics & Information Technology, 2008,30(5): 1222-1225.

[9] 史庭俊,桑霞,徐立杰,等.WSN中一种基于移动锚节点的节点定位算法［J］.软件学报,2009,20(增刊1):278-285. Shi Ting-jun,Sang Xia,Xu Li-jie,et al. A localization algorithm in wireless sensor networks with mobile anchor nodes［J］.Journal of Software, 2009,20(Suppl1):278-285.

[10] 周培德.计算几何-算法设计与分析［M］.3版.北京:清华大学出版社,1941:126-139.

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