Weighted centroid localization algorithm for WSNs based on K-means clustering point density

ZHANG Yi-zhu; ZHOU Li-zheng; TANG Rui; YU Min

doi:10.13873/J.1000-9787(2015)07-0125-03

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Weighted centroid localization algorithm for WSNs based on K-means clustering point density

更新时间：2025-09-11

- Weighted centroid localization algorithm for WSNs based on K-means clustering point density
- Vol. 34, Issue 7, Pages: 125-127+131(2015)
- 作者机构：
  
  1. 江西师范大学计算机信息工程学院
  2. 江西师范大学软件学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)07-0125-03
  CLC： TN929.5;TP212.9
- Published：2015
- 稿件说明：
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[1]张乙竹,周礼争,唐瑞,余敏.基于K-means聚类点密度的WSNs加权质心定位算法[J].传感器与微系统,2015,34(07):125-127+131.

ZHANG Yi-zhu, ZHOU Li-zheng, TANG Rui, et al. Weighted centroid localization algorithm for WSNs based on K-means clustering point density[J]. 2015, 34(7): 125-127+131.
[1]张乙竹,周礼争,唐瑞,余敏.基于K-means聚类点密度的WSNs加权质心定位算法[J].传感器与微系统,2015,34(07):125-127+131. DOI： 10.13873/J.1000-9787(2015)07-0125-03.

ZHANG Yi-zhu, ZHOU Li-zheng, TANG Rui, et al. Weighted centroid localization algorithm for WSNs based on K-means clustering point density[J]. 2015, 34(7): 125-127+131. DOI： 10.13873/J.1000-9787(2015)07-0125-03.

摘要

为降低无线传感器网络（WSNs）在节点众多时算法复杂度

提高定位精度

提出一种基于K—means聚类点密度的WSNs加权质心定位算法（KCPD—WCLA）。首先

对空间中随机大量布设的锚节点进行分组

利用三边测量定位法在二维平面上得到许多接近真实值的结果;然后将K—means聚类算法引入到WSNs的定位问题中

对K个聚类点密度加以考虑

利用加权质心定位算法（WCLA）得到定位结果。理论分析与仿真结果表明:计算复杂度明显降低

定位精度比多边定位算法（MLA）和WCLA有显著提高。

Abstract

In order to reduce wireless sensor networks（ WSNs） algorithm complexity when there are lots of anchor nodes

and improve positioning precision

propose a weighted centroid localization algorithm based on K-means clustering point density（ KCPD-WCLA）. First

group a large number of anchor nodes which are randomly deployed in space

and use trilateral measurement positioning method to obtain many results close to real value in twodimensional（ 2D） plane; then

K-means clustering algorithm is introduced to WSNs localization problem

take K clustering point density into consideration that position results can be achieved by using the weighted centroid localization algorithm（ WCLA）. Theoretical analysis and simulation results show that computational complexity is significantly reduced

positioning precision is improved significantly compared with multilateral localization algorithm（ MLA） and WCLA.

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references

无线传感器网络中多边定位的聚类分析改进算法 [J]. 孙大洋,钱志鸿,韩梦飞,王雪. 电子学报 . 2014(08)

无线传感器网络煤矿井下RSSI自适应定位算法 [J]. 曹开来,余敏. 传感器与微系统 . 2014(06)

基于RSSI的室内测距模型的研究 [J]. 朱明辉,张会清. 传感器与微系统 . 2010(08)

Determinants of aerosol lung-deposited surface area variation in an urban environment [J] . Cristina Reche,Mar Viana,Mariola Brines,Noemí Pérez,David Beddows,Andrés Alastuey,Xavier Querol. Science of the Total Environment . 2015

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