Improvement of weighted centroid localization algorithm for WSNs based on RSSI

DING En-jie1; QIAO Xin1; CHANG Fei1; QIAO Li3

doi:10.13873/j.1000-97872013.07.019

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Improvement of weighted centroid localization algorithm for WSNs based on RSSI

更新时间：2025-09-11

- Improvement of weighted centroid localization algorithm for WSNs based on RSSI
- Vol. 32, Issue 7, Pages: 53-56(2013)
- 作者机构：
  
  1. 中国矿业大学物联网(感知矿山)研究中心
  2. 中国矿业大学信息与电气工程学院
  3. 安徽医科大学第二附属医院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872013.07.019
  CLC： TN929.5;TP212.9
- Published：2013
- 稿件说明：
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[1]丁恩杰,乔欣,常飞,乔莉.基于RSSI的WSNs加权质心定位算法的改进[J].传感器与微系统,2013,32(07):53-56.

DING En-jie1, QIAO Xin1, CHANG Fei1, et al. Improvement of weighted centroid localization algorithm for WSNs based on RSSI[J]. 2013, 32(7): 53-56.
[1]丁恩杰,乔欣,常飞,乔莉.基于RSSI的WSNs加权质心定位算法的改进[J].传感器与微系统,2013,32(07):53-56. DOI： 10.13873/j.1000-97872013.07.019.

DING En-jie1, QIAO Xin1, CHANG Fei1, et al. Improvement of weighted centroid localization algorithm for WSNs based on RSSI[J]. 2013, 32(7): 53-56. DOI： 10.13873/j.1000-97872013.07.019.

摘要

针对无线传感器网络（WSNs）定位算法定位精度不高的问题

提出了一种基于RSSI测距的质心（Centroid）算法和加权质心（W-Centroid）定位算法相结合的新的定位方法 WR-Centroid。该算法主要通过RSSI测距得出4个参考节点到未知节点的距离

再任选3个距离为半径

以相应的参考节点为圆心画圆得到3个圆的交叠区域

构成一个三角形

求出这个三角形的质心。依照这种方法

求得4个质心坐标

利用加权质心定位算法求出未知节点的坐标。仿真结果表明:该算法比加权质心定位算法精度有很大的提高。

Abstract

Aiming at problem that positioning precision of wireless sensor networks（WSNs） localization algorithm is not high

a new positioning method（WR-Centroid） based on RSSI ranging combined centroid algorithm with weighted centroid positioning algorithm is proposed.The algorithm mainly through RSSI ranging obtain the distance from four reference nodes to unknown node

and then optionally three distances as a radius corresponding to the reference node as the circle center to draw circle and get the overlapping region of three circles

form a triangle

the centroid of the triangle is obtained.In accordance with this method

four centroid coordinates is obtained

using weighted centroid localization algorithm to calculate the unknown node coordinates.Simulation results show that the precision of this algorithm is greatly improved than the weighted centroid localization algorithm.

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references

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