期刊文献+

改进的局部保持典型相关分析的无线传感器网络节点定位方法 被引量:9

Improved Locality Preserving Canonical Correlation Analysis Node Localization Method in Wireless Sensor Networks
下载PDF
导出
摘要 利用接收信号强度(RSSI)进行无线传感器网络(WSN)定位是一类低成本定位方法。局部保持典型相关分析定位(LE-LPCCA)算法能通过节点间RSSI数据的相似度信息近似拟合WSN结构,取得了较高定位精度。但该算法只使用节点间相似性信息未保留信号空间和物理空间的相关性信息,且求解未知节点坐标时使用粗糙的质心法。针对以上问题,提出改进的局部保持典型相关分析定位(LE-ILPCCA)算法,该算法在样本训练阶段用平衡参数将数据的相似性和相关性信息进行融合,求取RSSI内在低维坐标表示的投影变换;在定位阶段,求解已知节点位置坐标和RSSI内在低维坐标之间存在的线性转换关系,获得未知节点的坐标。实验结果表明,本文算法与LE-LPCCA和LE-CCA相比定位精度高、稳定性强。 Location methods in wireless sensor networks(WSN)by received signal strength indicator(RSSI)are rela-tively inexpensive. Location Estimation-Locality Preserving Canonical Correlation Analysis(LE-LPCCA)can fit thestructure of WSN approximately using RSSI similarity among nodes and achieve high localization accuracy,but itonly uses data similarity while ignoring data dependency between signal and physical space,and employs rough cen-troid method. As to problems above,this paper proposes Location Estimation-Improved Locality Preserving Canoni-cal Correlation Analysis(LE-ILPCCA)method. In training phrase,it combines data similarity and dependency usinga balance parameter to compute more precise projection transformation of RSSI inner lower dimensional coordi-nates;in localization phrase,it calculates location of unknown nodes utilizing accurate transformational relation be-tween position coordinates and RSSI inner lower dimensional coordinates of known nodes. Experimental resultsshow that our method has a higher accuracy and stability than LE-LPCCA and LE-CCA.
作者 朱素文 曾宪华 胡梦 ZHU Suwen ZENG Xianhua HU Meng(College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China Chongqing Key Laboratory of Computational Intelligence, Chongqing 400065, China)
出处 《传感技术学报》 CAS CSCD 北大核心 2016年第10期1579-1588,共10页 Chinese Journal of Sensors and Actuators
基金 国家自然科学基金项目(61075019) 2015年重庆市研究生科研创新项目(CYS15173)
关键词 无线传感器网络 定位 典型相关分析 局部保持投影 wireless sensor networks localization canonical correlation analysis locality preserving projections
  • 相关文献

参考文献4

二级参考文献42

  • 1周祖德,胡鹏,刘泉,李方敏.一种基于MDS的无线传感器网络快速定位算法[J].传感技术学报,2007,20(10):2303-2307. 被引量:16
  • 2方震,赵湛,郭鹏,张玉国.基于RSSI测距分析[J].传感技术学报,2007,20(11):2526-2530. 被引量:265
  • 3王福豹,史龙,任丰原.无线传感器网络中的自身定位系统和算法[J].软件学报,2005,16(5):857-868. 被引量:672
  • 4何晓群,刘文卿.浅谈加权最小二乘法及其残差图——兼答孙小素副教授[J].统计研究,2006,23(4):53-57. 被引量:20
  • 5Liu Wenyuan, Wang Enshuang, Chen Zijun, et al. An Improved DV-Hop Loealizatinn Algorithm Based on tile Selection of Beacon Nodes [ J ]. Journal of Convergence Information Technology ,2010,5 (9) :157-164.
  • 6Doherty L, Pister K, El Ghaoui L. Convex Position Estimation It, Wireless Sensor Networks [C]//Proceedings of Joint Conference of the IEEE Computer and Communications Societies. USA, 2001: 1655-1663.
  • 7Bulusu N, Heidemann J, Fstrin D. GPS-Less Low-Cost Outdoor Localization for Very Small Devices [ J ]. IEEE Personal Communications ,2000,7 ( 5 ) :28-34.
  • 8Yi Shang, Rural W, Ying Zhang, et al. Localization from Mere Connectivity [ C ]//MobiHoc'03, Annapolis, Maryland, USA, 2003 : 201 -210.
  • 9Yi Shang, Ruml W. hnproved MDS-Based Localization [C]// INFOCOM'04, Hong Kong, China,2004:2640-2651.
  • 10Neal Patwari, Alfred O. Hero Ill. Manifold Learning Algorithm for Localization in Wireless Sensor Networks [C]//International of Conference Acoustics, Speed, and Signal Processing( ICASSP2004), Quebec, Canada, 2004:857-860.

共引文献60

同被引文献77

引证文献9

二级引证文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部