计算机应用 ›› 2013, Vol. 33 ›› Issue (11): 3016-3018.

• 网络与通信 • 上一篇    下一篇

可信邻居距离估计的DV-Hop校准算法

江禹生,陈跹,李萍   

  1. 重庆大学 通信工程学院,重庆 400044
  • 收稿日期:2013-05-27 修回日期:2013-07-17 出版日期:2013-11-01 发布日期:2013-12-04
  • 通讯作者: 陈跹
  • 作者简介:江禹生(1961-),男,重庆忠县人,博士,副教授,主要研究方向:无线传感网、物联网、宽带移动IP技术;陈跹(1989-),女,重庆梁平人,硕士研究生,主要研究方向:无线传感网;李萍(1987-),女,河南南阳人,硕士研究生,主要研究方向:无线传感网。
  • 基金资助:
    国家863计划项目

Calibration based DV-Hop algorithm with credible neighborhood distance estimation

JIANG Yusheng,CHEN Xian,LI Ping   

  1. College of Communication Engineering, Chongqing University, Chongqing 400044, China
  • Received:2013-05-27 Revised:2013-07-17 Online:2013-12-04 Published:2013-11-01
  • Contact: CHEN Xian

摘要: 针对DV-Hop算法定位精度低的问题,提出了可信邻居距离估计的DV-Hop(CDV-Hop)校准算法。通过将邻居节点间距离与连通性差异联系起来,定义了一种新的邻居距离估计方法,计算出更精确的邻居距离;根据不同未知节点与其最近锚节点独特的位置关系,增加了校准步骤,以可信邻居距离为校准标准对未知节点的估计位置进行修正。仿真结果表明,CDV-Hop算法在不同的网络环境下表现稳定,随着锚节点比例的增加,与DV-Hop算法相比,定位精度提高了4.57%~10.22%,与改进的DV-Hop(IDV-Hop)算法相比,定位精度提高了3.2%~8.93%。

关键词: 无线传感器网络, 定位, DV-Hop算法, 邻居距离, 连通性差异

Abstract: Concerning the poor localization precision of Distance Vector-Hop (DV-Hop), a calibration based DV-Hop algorithm with credible neighborhood distance estimation (CDV-Hop) was proposed, which defined a new measure to estimate the neighborhood distances by relating the proximity of two neighbors to their connectivity difference, and then calculated the more accurate neighborhood distances. According to the unique location relationship between the unknown nodes and their nearest anchor nodes, this algorithm added the calibration step, which took the credible neighborhood distances as the calibration standard to correct the position of unknown nodes. The simulation results show that the CDV-Hop algorithm works stably in different network environment. With the ratio of anchor nodes increasing, there is an improvement of 4.57% to 10.22% in localization precision compared with DV-Hop algorithm and 3.2% to 8.93% in localization precision compared with Improved DV-Hop (IDV-Hop) algorithm.

Key words: Wireless Sensor Network (WSN), localization, DV-Hop algorithm, neighborhood distance, connectivity difference

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