改进PSA的3维WSN定位算法  

Improved PSA for 3D WSN Localization Algorithm

作　　者：余修武 张正凌 刘永 YU Xiuwu;ZHANG Zhengling;LIU Yong(School of Resources Environment and Safety Engineering,University of South China,Hengyang 421001,China;School of Electronic Engineering,University of South China,Hengyang 421001,China;College of Physics and Optoelectronic Engineering,Shenzhen University,Shenzhen 518000,China)

机构地区：[1]南华大学资源环境与安全工程学院,湖南衡阳421001 [2]南华大学电气工程学院,湖南衡阳421001 [3]深圳大学物理与光电工程学院,广东深圳518000

出　　处：《工程科学与技术》2025年第2期22-28,共7页Advanced Engineering Sciences

基　　金：湖南省自然科学基金项目(2024JJ5338);国家自然科学基金项目(11875164)。

摘　　要：针对传统3维DV-Hop定位算法在定位无线传感器网络节点中存在定位误差高、不稳定等问题,提出一种改进PSA的3维WSN定位算法,即IPLA算法。首先,在获取最小跳数过程中,IPLA算法采用双通信半径细化跳数,以降低误差;然后,在获取最优跳距的过程中,建立融合距离加权系数的目标函数,设计改进的PSA算法(IPSA)求解最优跳距,并使用混沌映射改进PSA算法搜索种群初始化,提高算法迭代能力以及减少拓扑结构改变产生的距离估计误差;最后,在获取未知节点过程中,建立含权重的目标函数,再次采用改进的PSA算法获取最终估计坐标,以提升寻优速率并降低定位误差。在不同场景中,将提出的IPLA算法与传统3维DV-Hop算法及其他算法进行算法迭代性、定位误差的仿真对比实验,结果表明,IPLA算法具有更低的归一化误差、更好的寻优曲线。IPLA算法在降低无线传感器定位误差方面有较好的效果及收敛性。Objective This study proposes an improved 3D WSN localization algorithm with an enhanced particle swarm algorithm(PSA)to address the high positioning errors and instability encountered with the traditional 3D DV-Hop localization algorithm in locating wireless sensor network nodes.The proposed improved particle localization algorithm(IPLA)specifically targets and mitigates the error steps inherent in the traditional 3D DV-Hop localization process.Methods Firstly,in the traditional method,the nodes within the communication radius were considered as 1-hop,which caused the hop count calculation to be insufficiently refined and produced a significant error.In contrast,this study adopted a dual communication radius,broadcasted at R and R/2,respectively,to refine the hop count calculation and obtain the minimum hop count with a much smaller error.Secondly,the calculation of the average hopping distance in the traditional method was based on the topology of a linearly distributed wireless sensor network.The average hopping distance calculated by this method affected the accuracy of the localization.Therefore,a fitness function with a distance weighting factor was established.The improved PSA algorithm with meta-starting was used for the solution,and the introduction of chaotic mapping into the PSA algorithm enhanced the algorithm’s optimization capability and reduced the error in obtaining the average hopping distance.Finally,for the problem of large errors in obtaining node coordinates by the least squares method of the traditional method,an adaptation function with weights was established to reduce the error existing in the topology.The improved PSA algorithm was again employed in this paper instead of the least squares method,which was the traditional method,to further improve the accuracy of locating the nodes.Simulation experiments were conducted in different scenarios to compare the proposed IPLA algorithm with the traditional 3-dimensional DV-Hop algorithm,DBO algorithm,and WBOA algorithm in terms of localizatio

关 键 词：无线传感器网络 3维WSN定位 混沌映射 双通信半径 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]