航空科学技术2024，Vol.35Issue(12)：54-59,6.DOI:10.19452/j.issn1007-5453.2024.12.007
基于改进粒子群优化算法的机身室内指纹定位研究
Fuselage Indoor Fingerprint Localization Method Based on Improved Particle Swarm Optimization Algorithm
摘要
Abstract
Ground testing for aircraft structural strength is a critical part of aircraft manufacturing.It is of great significance to safeguard the safety of personnel,enhance the performance,and reduce the cost.In order to improve the testing efficiency and obtain a higher positioning accuracy in indoor testing environment,this paper integrates the dual variational particle swarm optimization(DMPSO)algorithm into indoor wireless positioning,proposes an indoor fingerprint positioning method for aircraft fuselage structure strength test based on improved particle swarm optimization algorithm,and verifies its validity through experiments.The results show that compared with the traditional particle swarm optimization(PSO)algorithm and the maximum likelihood estimation(MLE)algorithm,the DMPSO proposed in this paper performs well in terms of average localization error(0.4341m),which is significantly better than that of the PSO of 0.7263m and MLE of 0.8089m.Therefore,the DMPSO method has higher localization accuracy and stability.The research of this paper not only provides a new approach for aircraft structural strength testing,but also provides an effective solution to improve the positioning accuracy of indoor wireless positioning.关键词
机身结构强度测试/室内定位/改进粒子群优化算法/DMPSO/定位误差Key words
aircraft structure strength test/indoor localization/Improved particle swarm optimization algorithm/DMPSO/positioning error分类
信息技术与安全科学引用本文复制引用
毕杨,张杨梅,刘坤,李军芳..基于改进粒子群优化算法的机身室内指纹定位研究[J].航空科学技术,2024,35(12):54-59,6.基金项目
航空科学基金(201809T7001,2019ZH0T7001) Aeronautical Science Foundation of China(201809T7001,2019ZH0T7001) （201809T7001,2019ZH0T7001）
