改进的无线传感器网络无偏距离估计与节点定位算法

魏全瑞; 刘俊; 韩九强

doi:10.7652/xjtuxb201406001

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改进的无线传感器网络无偏距离估计与节点定位算法

更新时间：2025-07-09

- 改进的无线传感器网络无偏距离估计与节点定位算法
- An Improved DVhop Node Localization Algorithm Based on Unbiased Estimation for Wireless Sensor Networks
- 西安交通大学学报 2014年48卷第6期页码：1-6
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
  
  : 2013-12-09。作者简介: 魏全瑞(1984—),男,博士生;刘俊(通信作者),男,讲师。基金项目: 国家自然科学基金资助项目(61105021,61071217);教育部高等学校博士学科点专项科研基金资助项目(20110201110010)
- DOI：10.7652/xjtuxb201406001
  中图分类号： TP393
- 网络首发：2014-06-10，
  
  纸质出版：2014
- 稿件说明：
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魏全瑞, 刘俊, 韩九强. 改进的无线传感器网络无偏距离估计与节点定位算法[J]. 西安交通大学学报, 2014,48(6):1-6.

An Improved DVhop Node Localization Algorithm Based on Unbiased Estimation for Wireless Sensor Networks[J]. 2014, 48(6): 1-6.
魏全瑞, 刘俊, 韩九强. 改进的无线传感器网络无偏距离估计与节点定位算法[J]. 西安交通大学学报, 2014,48(6):1-6. DOI： 10.7652/xjtuxb201406001.

An Improved DVhop Node Localization Algorithm Based on Unbiased Estimation for Wireless Sensor Networks[J]. 2014, 48(6): 1-6. DOI： 10.7652/xjtuxb201406001.

摘要

针对无线传感器网络中基于跳数的节点定位算法不能满足无偏距离估计、节点定位误差大的问题

提出了一种改进的无偏距离估计与节点定位算法(UEDV-hop

Unbiased Estimation DV-hop)。该算法分析期望距离和跳数的关系

建立一种新的期望距离与跳数模型

根据节点通信半径是否已知分别推导了两种UEDV-hop的求解形式。仿真实验结果表明:所提的两种UEDV-hop算法的估计距离在不同跳数时都近似等于该跳期望距离

算法在距离估计和节点定位精度上相对于DV-hop(Distance Vector-hop)算法及基于最小二乘法改进的DV-hop算法都有较大提高

在节点数目等于2 500时

UEDV-hop算法的估计距离误差比DV-hop算法降低了9.5%

定位精度提高了55%。

Abstract

An improved DV hop localization algorithm based on unbiased estimation is proposed to obtain the unbiased estimation of distance and to reduce the localization error of existing node localization methods based on hop count for wireless sensor networks. A modified model of the relationship between expected distance and hop count is established through analyzing the hop progress information for different hop counts; Two approaches for the solution of UEDV hop method are derived

according to whether node communication radiuses are known. Simulation results and comparisons with the DV hop and the DV hop(LS)algorithms show that the distance estimated by the UEDV hop is approximately equal to the expectation distance

and that the estimation error and the localization accuracy of the UEDV hop are improved significantly. A comparison to the DV hop with 2 500 nodes shows that the distance estimation error of the UEDV hop is reduced by 9.5%

and the localization accuracy is improved by 55%.

关键词

Keywords

references

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