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 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.展开更多
基金supported by the Aviation Science Foundation(ASFC-20181352009).
文摘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.
