[1]徐晓菊,唐 翔,黄为勇.一种基于RSSI的煤矿井下WSN节点快速定位算法[J].南京师大学报(自然科学版),2014,37(04):158.
 Xu Xiaoju,Tang Xiang,Huang Weiyong.A Fast Node Localization Algorithm for Coal-mine UndergroundBased on RSSI[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(04):158.
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一种基于RSSI的煤矿井下WSN节点快速定位算法()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
第37卷
期数:
2014年04期
页码:
158
栏目:
计算机科学
出版日期:
2014-12-31

文章信息/Info

Title:
A Fast Node Localization Algorithm for Coal-mine UndergroundBased on RSSI
作者:
徐晓菊唐 翔黄为勇
徐州工程学院信电工程学院,江苏 徐州 221111
Author(s):
Xu XiaojuTang XiangHuang Weiyong
School of Information and Electrical Engineering,Xuzhou Institute of Technology,Xuzhou 221111,China
关键词:
无线传感器网络煤矿井下节点定位接收信号强度指示高斯滤波量子粒子群优化算法
Keywords:
wireless sensor networks(WSN)coal-mine underground node localizationreceived signal strength indicator(RSSI)Gauss filterquantum-behaved particle swarm optimization(QPSO)
分类号:
TP393
文献标志码:
A
摘要:
为提高煤矿井下传感器网络节点定位的实时性,提出了一种基于接收信号强度(RSSI)的快速定位算法.该算法在井下巷道锚节点双链式部署结构的基础上,运用高斯密度函数对节点接收到的锚节点信号强度最大的RSSI信号进行滤波处理,再应用指数因子和滤波后RSSI值直接计算确定未知节点的坐标.指数因子采用一种改进的量子粒子群优化算法及定位均方根误差最小的准则进行优化.所提出的算法具有定位速度快、计算量小的优点,仿真实验结果验证了算法的可行性与有效性,适用于煤矿井下无线传感器网络实时定位系统中.
Abstract:
To improve the realtime performance of node localizationin in coal-mine underground wireless sensor networks,a fast node localization algorithm based on RSSI is proposed.On the base of the double-chain deployment structure of anchor nodes in coal-mine underground,the largest RSSI signals received from the anchor nodes are processed by the filter with Gauss density function,and the coordinates of the unknown nodes are calculated directly by the filtered RSSI signals and exponential factors.The exponential factors are optimized by an improved quantum-behaved particle swarm optimization algorithm and the criterion of the root mean square error minimum.The algorithm proposed has the advantage of fast positioning speed and low computational complexity and the simulation results verify the feasibility and effectiveness of the algorithm,which can be suitable for real time positioning system in coal mine underground wireless sensor networks.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-08-16.
基金项目:国家自然科学基金(51274202)、江苏省高校自然科学研究重大项目(13KJA520007)、江苏省基础研究计划(BK20131124)、江苏省高校自然科学研究项目(12KJD510013).
通讯联系人:徐晓菊,讲师,研究方向:无线传感器网络、矿井通信及监控.E-mail:xiaoju_xu@163.com
更新日期/Last Update: 2014-12-31