计算机与数字工程2026，Vol.54Issue(3)：589-594,606,7.DOI:10.3969/j.issn.1672-9722.2026.03.001
基于混沌映射改进蝙蝠优化的DV-Hop定位算法
Improved DV-Hop Localization Algorithm for Bat Optimization Based on Chaotic Mapping
摘要
Abstract
Aiming at the low localization accuracy of DV-Hop algorithm,an improved DV-Hop localization algorithm based on chaotic mapping is proposed.The algorithm is mainly optimized in two aspects,which are solving average hop distance and esti-mating node position.Firstly,the average hop distance is reconstructed according to the minimum mean square error criterion and the correction factor is set to reduce the ranging error.Secondly,logistic chaos mapping is used to change population distribution and increase population diversity.Two new position update strategies are adopted to enhance global search ability,formulate local search strategies,and set parameter factors to control search scope to improve search accuracy.Finally,chaotic mapping improved Bat algorithm(CEMBA)is used to solve the coordinates of unknown nodes.The simulation results show that the proposed ICEM-BADV-Hop algorithm has the minimum positioning error and superior positioning performance compared with DV-Hop algorithm,MDV-Hop algorithm,BADV-Hop algorithm and PSODV-Hop algorithm in both isotropic and anisotropic networks with the same parameters.关键词
无线传感器网络/节点定位/蝙蝠算法/DV-Hop算法/混沌映射Key words
wireless sensor network/node positioning/bat algorithm/DV-Hop algorithm/chaotic mapping分类
信息技术与安全科学引用本文复制引用
董玉,张治中,冯姣..基于混沌映射改进蝙蝠优化的DV-Hop定位算法[J].计算机与数字工程,2026,54(3):589-594,606,7.基金项目
国家自然科学基金项目(编号:61501244,61501245) （编号:61501244,61501245）
江苏省自然科学基金项目(编号:BK20150932)资助. （编号:BK20150932）
