计算机应用 ›› 2015, Vol. 35 ›› Issue (5): 1273-1275.DOI: 10.11772/j.issn.1001-9081.2015.05.1273

• 先进计算 • 上一篇    下一篇

改进的狭长空间中加权质心定位算法

刘勇, 张锦龙, 张彦波, 王韬   

  1. 河南大学 物理与电子学院, 河南 开封 475000
  • 收稿日期:2014-12-10 修回日期:2015-01-04 出版日期:2015-05-10 发布日期:2015-05-14
  • 通讯作者: 张锦龙
  • 作者简介:刘勇(1989-),男,湖南益阳人,硕士研究生,主要研究方向:无线传感器网络; 张锦龙(1977-),男,河南开封人,副教授,博士,主要研究方向:无线传感器网络、光传感; 张彦波(1979-),男,河南安阳人,副教授,博士,主要研究方向:无线传感器网络、通信与信息系统; 王韬(1988-),男,河南信阳人,硕士研究生,主要研究方向:无线传感器网络.
  • 基金资助:

    国家自然科学基金资助项目(60677003);教育部新世纪优秀人才支持计划(NECT-12-0111).

Improved weighted centroid localization algorithm in narrow space

LIU Yong, ZHANG Jinlong, ZHANG Yanbo, WANG Tao   

  1. School of Physics and Electronics, Henan University, Kaifeng Henan 475000, China
  • Received:2014-12-10 Revised:2015-01-04 Online:2015-05-10 Published:2015-05-14

摘要:

针对目前狭长空间环境中信号多路径效应明显、传感器节点定位精度不足等情况,提出了一种基于信号接收强度(RSSI)的加权质心定位算法.该算法根据狭长带状区域环境特点部署信标节点,通过相邻信标节点的实际距离和信号接收强度,动态获取周围环境的路径衰落指数,提高RSSI测距算法的环境适应能力;根据当前环境改进加权质心算法的加权因子,引入修正因子,进一步提高算法的定位精度.理论分析和仿真结果表明,该算法设计优化,适应于狭长空间环境,宽度分别为3 m、5 m、8 m、10 m,信标节点的个数为10的巷道环境中,其定位计算精度比传统加权质心算法分别提高了22.1%、19.2%、16.1%、16.5%,稳定性分别提高了23.4%、21.5%、18.1%、15.4%.

关键词: 无线传感器网络, 信号接收强度, 信标节点, 定位, 加权质心算法

Abstract:

Concerning the problem that severe signal multipath effect, low accuracy of sensor node positioning, etc. in narrow space, a new method using Weighted Centroid Localization (WCL) algorithm based on Received Signal Strength Indicator (RSSI) was proposed. The algorithm was used in scenarios with characteristics of long and narrow strip space, and it could dynamically acquire the decline index of path by RSSI and distance of neighbor beacon node signal, improve the environmental adaptation of RSSI distance detection algorithm. In addition, the algorithm based on environment improved weight coefficient of weighted centroid algorithm by introducing correction factor, which improved the accuracy of localization. Theoretical analysis and simulation results show that the algorithm has been optimized to adapt to narrow space. As compared with the Weighted Centroid Localization (WCL) algorithm, in roadway environment with the width of 3 m, 5 m, 8 m, 10 m respectively and 10 beacon nodes, positioning precision increases 22.1%, 19.2%, 16.1% and 16.5% respectively, the stability increases 23.4%, 21.5%, 18.1% and 15.4% respectively.

Key words: Wireless Sensor Network (WSN), Received Signal Strength Indicator (RSSI), beacon node, localization, Weighted Centroid Localization (WCL) algorithm

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