[1]徐迪 刘瑞兰.基于QPSO算法的无线传感器定位研究[J].计算机技术与发展,2012,(02):41-44.
　XU Di,LIU Rui-lan.Wireless Sensor Networks Location Study Based on QPSO[J].,2012,(02):41-44.
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基于QPSO算法的无线传感器定位研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年02期
页码:
41-44
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Wireless Sensor Networks Location Study Based on QPSO
文章编号:
1673-629X（2012）02-0041-04
作者:
徐迪 刘瑞兰
南京邮电大学
Author(s):
XU Di; LIU Rui-lan
Nanjing University of Posts and Telecommunications
关键词:
无线传感器网络; 量子粒子群算法; 定位; QPSO-RSSI
Keywords:
WSN;  PSO;  localization;  QPSO-RSSI
分类号:
TP31
文献标志码:
A
摘要:
网络节点采集的数据、对目标的追踪、网络拓扑管理等都需要确定的位置信息才有意义,因此节点自定位技术是大多数应用的基础和前提。RSSI测距技术广泛应用于WSN节点定位中,但其测距误差较大,直接导致节点自身定位精度不高。针对此类情况,文中通过对无线电传播路径损耗模型以及大量实测数据的分析,提出了一种基于误差校正的定位优化算法。利用量子粒子群优化算法将存在偏差LQI值进行优化,从而对误差进行补偿。实验结果表明,量子机制的引入解决了局部优化的问题,同时使原有算法的优化性能得到一定程度的提高,具有普遍应用意义
Abstract:
Since the data collection,object tracking and mesh topology managing is significant only when the positions of corresponding sensor nodes have been identified,therefore,as one of the core technologies,the nodes locating plays a pivotal role in the WSN application.WSN nodes which placed in application environment always get some affect by environment.For such case,by analyzing the model of radio wave propagation loss and empirical data from real measurement,a localization algorithm based on error correction is provided in this paper.Use QPSO-RSSI which based on particle swarm optimization（QPSO） to optimize a number of LQI（which exist some deviation）which unknow node received from sink node,this can compensate the deviation.Then transform from LQI to RSSI to get distance.The consequence of experiment shows that this algorithm can improve accuracy of location,can be applied to many applications

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备注/Memo

备注/Memo:
南京邮电大学攀登计划项目（NY207057）徐迪（1985-），女，硕士研究生，研究方向为网络传感器和传感器网络；刘瑞兰，博士，硕士生导师，副教授，研究方向为智能软测量技术以及网路传感器与传感器网路
更新日期/Last Update: 1900-01-01