复杂环境下多策略改进麻雀搜索的定位算法  

Multi-strategy Improved Sparrow Search Positioning Algorithm in Complex Environment

作　　者：王磊[1] 崔嵩 牛婷婷 WANG Lei;CUI Song;NIU Tingting(College of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454000,China)

机构地区：[1]河南理工大学计算机科学与技术学院,河南焦作454000

出　　处：《小型微型计算机系统》2024年第11期2768-2776,共9页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(52174109)资助;河南省科技攻关项目(212102210092)资助;河南省高校重点研究基金项目(20A520015)资助.

摘　　要：为了提高传统DV-HOP(Distance vector hop)算法在三维复杂环境场景下的节点定位精度,提出了一种利用多策略改进麻雀搜索算法优化的3D-DVHop定位算法.首先通过重新定义距离加权因子划分最优跳数,其次利用距离相似链路法来修正节点间的跳数大小,最后采用麻雀搜索算法实现3D-DVHop算法未知节点的位置寻优,并通过优化位置控制因子,同时引入蝴蝶搜索算法和自适应的局部搜索策略,增强麻雀搜索算法初始种群的多样性以及全局收敛速度和跳出局部最优的能力.仿真结果表明,该算法与传统DV-Hop算法以及其他同类算法相比,具有更好的稳定性和更高的定位精度.In order to improve the node localization accuracy of the traditional DV-HOP(Distance vector hop)algorithm in 3D complex environment scenes,a 3D-DVHop localization algorithm optimized using a multi-strategy improved sparrow search algorithm is proposed.Firstly,the optimal number of hops is divided by redefining the distance weighting factor.Secondly the distance similar link method is used to correct the hop size between nodes.Finally,the sparrow search algorithm is used to implement the location finding of unknown nodes of the 3D-DVHop algorithm,and the initial population diversity of the sparrow search algorithm as well as the global convergence speed and the ability to jump out of the local optimum are enhanced by optimising the location control factor,while introducing the butterfly search algorithm and the adaptive local search strategy.Simulation results show that the algorithm has better stability and higher localisation accuracy than the traditional DV-Hop algorithm and other similar algorithms.

关 键 词：无线传感网络 3DDV-Hop 跳数修正 麻雀搜索算法 复杂环境 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]