基于测距修正及改进灰狼优化器的DV-Hop定位算法研究

doi:10.11959/j.issn.2096-3750.2021.00222

物联网学报 ›› 2021, Vol. 5 ›› Issue (4): 62-70.doi: 10.11959/j.issn.2096-3750.2021.00222

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¹^,², 吴帅¹^,², 高传义¹^,², 李宁¹^,², 李波东¹^,², 杨小勇²^,³

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；

修回日期:2021-11-08 出版日期:2021-12-30 发布日期:2021-12-01
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
基金资助:
国家自然科学基金-雅砻江联合基金资助项目(U1965102);西安市科技计划项目(201806117YF05NC13-2);陕西省创新人才推进计划-物联网科技创新团队(2019TD-028)

Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer

Xiaoqiang ZHAO¹^,², Shuai WU¹^,², Chuanyi GAO¹^,², Ning LI¹^,², Bodong LI¹^,², Xiaoyong YANG²^,³

¹ Xi'an University of Posts and Telecommunications, Xi'an 710121, China
² Shaanxi Provincial Key Laboratory of Information Communication Network and Security, Xi'an, 710121, China
³ National Institute of Radio Spectrum Management, Xi'an 710061, China

Revised:2021-11-08 Online:2021-12-30 Published:2021-12-01
Supported by:
The Yalong River Joint Funds of the National Natural Science Foundation of China(U1965102);The Science and Technology Project of Xi’an(201806117YF05NC13-2);The IoT Innovation Team for Talent Promotion Plan of Shaanxi Province(2019TD-028)

摘要/Abstract

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。

关键词: 无线传感器网络, 节点定位, DV-Hop算法, 灰狼优化器

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.

Key words: wireless sensor network, node location, DV-Hop algorithm, gray wolf optimizer

中图分类号:

TP393

赵小强, 吴帅, 高传义, 李宁, 李波东, 杨小勇. 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, Ning LI, Bodong LI, Xiaoyong YANG. 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.

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算法参数	参数意义	默认值
BorderLength	节点分布区域大小	100 m×100 m×100 m
NodeAmount	节点总数	100个
BeaconAmount	锚节点数量	30个
UNAmount	未知节点数量	70个
R	通信半径	30 m
Iteration	仿真次数（取20次仿真平均值）	20次

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

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