Improved adaptive genetic algorithm based RFID positioning

作     者：LI Yu WU Honglan SUN Youchao LI Yu;WU Honglan;SUN Youchao

作者机构：Civil Aviation CollegeNanjing University of Aeronautics and AstronauticsNanjing 211100China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2022年第33卷第2期

页      面：305-311页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081104[工学-模式识别与智能系统] 0804[工学-仪器科学与技术] 0714[理学-统计学（可授理学、经济学学位）] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported by the Aviation Science Foundation(ASFC-20181352009). 

主　　题：radio frequency identification(RFID)positioning im-proved genetic algorithm Gaussian filter passive tags 

摘      要：The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align the passive tag ar-rays.We use chaotic sequences to generate the intersection points,the weakest single point intersection is used to ensure the convergence accuracy of the algorithm while avoiding the optimization jitter problem.Meanwhile,to avoid the problem of slow convergence and immature convergence of the algorithm caused by the weakening of individual competition at a later stage,we use adaptive rate of change to improve the optimiza-tion efficiency.In addition,to remove signal noise and outliers,we preprocess the data using Gaussian filtering.Experimental results demonstrate that the proposed algorithm achieves high-er localization accuracy and improves the convergence speed.