基于多种策略共同改进DV-Hop定位算法研究  

Research on Improving DV-Hop Localization Algorithmbased on Multiple Strategies

作　　者：田祎然 TIAN Yiran(School of Physics and Electrical Engineering,Mudanjiang Normal University,Mudanjiang 157011,China)

机构地区：[1]牡丹江师范学院物理与电子工程学院,黑龙江牡丹江157011

出　　处：《牡丹江师范学院学报(自然科学版)》2025年第1期26-29,共4页Journal of Mudanjiang Normal University:Natural Sciences Edition

基　　金：黑龙江省基本科研业务费项目(1454QN016);黑龙江省自然科学基金项目(LH2019E126)。

摘　　要：提出基于多种策略共同改进的DV-Hop定位算法,简称TNGODV-Hop.该算法加入Tent混沌映射初始化种群,采用混合反向学习策略优化北方苍鹰算法,计算未知节点的坐标.仿真实验结果表明,经过多策略共同改进的DV-Hop定位算法,在精度上取得了显著的提升.In this paper,we propose an improved DV-Hop localization algorithm based on multiple strategies,abbreviated as TNGODV-Hop.The algorithm is added to the initial population of the Tent chaotic map and adopts a mixed reverse learning strategy to optimize the Northern Goshawk algorithm and calculate the coordinates of unknown nodes.The simulation results show that the DV-Hop localization algorithm,which was improved by multiple strategies,has achieved a remarkable improvement in accuracy.

关 键 词：无线传感器网络 DV-HOP定位算法 北方苍鹰优化算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]