Improved adaptive genetic algorithm based RFID positioning  

作　　者：LI Yu WU Honglan SUN Youchao 

机构地区：[1]Civil Aviation College,Nanjing University of Aeronautics and Astronautics,Nanjing 211100,China

出　　处：《Journal of Systems Engineering and Electronics》2022年第2期305-311,共7页系统工程与电子技术（英文版）

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

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.

关 键 词：radio frequency identification(RFID)positioning im-proved genetic algorithm Gaussian filter passive tags 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP391.44[自动化与计算机技术—控制科学与工程]