基于测距修正及改进灰狼优化器的DV-Hop定位算法研究

赵小强; 吴帅; 高传义; 李宁; 李波东; 杨小勇

doi:10.11959/j.issn.2096-3750.2021.00222

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基于测距修正及改进灰狼优化器的DV-Hop定位算法研究

理论与技术 | 更新时间：2024-06-05

- 基于测距修正及改进灰狼优化器的DV-Hop定位算法研究
- Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer
- 物联网学报 2021年5卷第4期页码：62-70
- 作者机构：
  
  1. 西安邮电大学，陕西西安 710021
  2. 陕西省信息通信网络及安全重点实验室，陕西西安 710121
  3. 国家无线电频谱管理研究所，陕西西安 710061；
- 作者简介：
  
  [ "赵小强（1977−2021），男，博士，西安邮电大学教授，主要研究方向为物联网技术及应用" ]
  [ "吴帅（1994− ），男，西安邮电大学硕士生，主要研究方向为物联网技术及应用" ]
  [ "高传义（1994− ），男，西安邮电大学硕士生，主要研究方向为物联网技术及应用" ]
  [ "李宁（1995− ），男，西安邮电大学硕士生，主要研究方向为物联网技术及应用" ]
  [ "李波东（1997− ），男，西安邮电大学硕士生，主要研究方向为物联网技术及应用" ]
  [ "杨小勇（1975− ），男，国家无线电频谱管理研究所高级工程师，主要研究方向为无线电监测、测向、定位和信号分析等" ]
- 基金信息：
  
  国家自然科学基金-雅砻江联合基金资助项目;The Yalong River Joint Funds of the National Natural Science Foundation of China(U1965102);西安市科技计划项目;The Science and Technology Project of Xi’an(201806117YF05NC13-2);陕西省创新人才推进计划-物联网科技创新团队;The IoT Innovation Team for Talent Promotion Plan of Shaanxi Province(2019TD-028)
- DOI：10.11959/j.issn.2096-3750.2021.00222
  中图分类号： TP393
- 纸质出版日期：2021-12-30，
  
  网络出版日期：2021-12，
- 稿件说明：
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赵小强, 吴帅, 高传义, 等. 基于测距修正及改进灰狼优化器的DV-Hop定位算法研究[J]. 物联网学报, 2021,5(4):62-70.

XIAOQIANG ZHAO, SHUAI WU, CHUANYI GAO, et al. Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer. [J]. Chinese journal on internet of things, 2021, 5(4): 62-70.
赵小强, 吴帅, 高传义, 等. 基于测距修正及改进灰狼优化器的DV-Hop定位算法研究[J]. 物联网学报, 2021,5(4):62-70. DOI： 10.11959/j.issn.2096-3750.2021.00222.

XIAOQIANG ZHAO, SHUAI WU, CHUANYI GAO, et al. Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer. [J]. Chinese journal on internet of things, 2021, 5(4): 62-70. DOI： 10.11959/j.issn.2096-3750.2021.00222.

摘要

节点定位是无线传感器网络中的一个重要问题，基于测距的定位算法虽然定位误差较小，但在应用于室外三维环境时具有较多的局限性。因此，以原始的距离向量（DV-Hop

distance vector-hop）算法为研究基础，分别引入接收信号强度指示（RSSI

received signal strength indication）算法和最小均方误差（MMSE

minimum mean squared error）准则对算法的测距过程进行修正，同时采用改进的灰狼优化器对确定未知节点坐标的过程进行优化处理。仿真结果表明，相较于原始DV-Hop算法和IPDV-Hop算法，IGDV-Hop算法在初始参数下的平均定位误差率分别降低了28%和17%，定位效果得到明显改善。

Abstract

Node location is an important problem in wireless sensor network.Although the location algorithm based on distance measurement has small positioning error

it has many limitations when applied to outdoor environments.Therefore

based on the original distance vector-hop (DV-Hop) algorithm

received signal strength indication (RSSI) technology and the minimum mean square error (MMSE) criterion to modify the algorithm’s ranging process were introduced

and the improved gray wolf optimizer was used to optimize the process of determining the coordinates of unknown nodes.Simulation results show that

compared with the original DV-Hop algorithm and IPDV-Hop algorithm

the average location error rate of the IGDV-Hop algorithm under the initial parameters was reduced by 28% and 17% respectively

and the location effect was significantly improved.

关键词

无线传感器网络节点定位DV-Hop算法灰狼优化器

Keywords

wireless sensor networknode locationDV-Hop algorithmgray wolf optimizer

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