基于自适应差分粒子群优化的DV-Hop定位算法  

DV-Hop localization algorithm based on adaptive differential particle swarm optimization

作　　者：朱子行 陈辉[1] 王旭 ZHU Zihang;CHEN Hui;WANG Xu(School of Computer Science and Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China)

机构地区：[1]安徽理工大学计算机科学与工程学院,安徽淮南232001

出　　处：《阜阳师范大学学报（自然科学版）》2023年第1期72-78,共7页Journal of Fuyang Normal University:Natural Science

基　　金：国家自然科学基金(61170060);安徽省教育厅重点教学研究项目(2020jyxm0458)。

摘　　要：针对常规DV-Hop算法存在定位精确度偏低,难以满足高精度定位应用的需求等问题,提出一种基于自适应差分粒子群优化的DV-Hop定位算法。该算法首先利用节点间RSSI值实现跳数计算的精确化,然后引入跳距可信度提高平均跳距的计算精度,最后利用自适应差分粒子群优化算法来估计未知节点的位置。实验结果表明,在不同节点数量、通信半径以及锚节点数三种情况下,改进后算法的节点定位精确度相比于传统DV-hop定位算法分别提高了45.3%、42.9%和39.7%。For the problems of the traditional DV-Hop algorithm existing low positioning accuracy and difficulties to meet the needs of high-precision positioning applications,a DV-Hop location algorithm based on adaptive difierential particle swarm optimization(ADP-DV-Hop)is proposed.First of all,the RS SI value between nodes is used to achieve the precision of hop count calculation,then hop distance reliability averaging method to improve the calculation accuracy of the average hop distance is introduced,and finally the adaptive differential particle swarm is used to estimate the position of unknown nodes.Simulation results show that in the case of different nodes,dififerent communication radius and different anchor nodes,the node positioning accuracy of the improved algorithm is increased by 45.3%,42.9%and 39.7%respectively,compared with the traditional DV-Hop location algorithm.

关 键 词：无线传感器网络 DV-HOP算法 粒子群算法 差分进化算法 

分 类 号：TN934[电子电信—信号与信息处理]