Research On RFID Tag Recognition Algorithm In Single Reader Mobile Environment Based On Tail Code Environment Perception

In recent years,the Internet of Things has developed rapidly.Radio Frequency Identification(RFID)technology,as one of the key technologies of the Internet of Things,is currently widely used in many areas such as warehouse logistics automation management,monitoring system of ecological environment and natural disaster to accelerate the implementation of information and digital development.In RFID system,the reader interacts with tags in its signal area.In small-medium regions dynamic RFID scenarios where a single reader moves at a constant speed along a fixed trajectory,previous studies have paid less attention to the effect of dynamic parameters on the system,making it difficult existing performance evaluation indexes to assess the performance of the system.And the existing tag recognition algorithms have insufficient tag recognition ratios.This paper conducts research based on the above issues,and the specific research contents are as follows:(1)This paper studies a performance evaluation method of single reader movement RFID system(SRMRS).First,the dynamic parameter model of SRMRS is build.Then,Framed Slotted ALOHA Protocol,Dynamic Framed Slotted ALOHA Protocol and EPCC1G2 algorithms are applied to the system to simulate the working process of dynamic system.Finally,the effects of various parameters on tag loss ratio and total identification lap number are analyzed by comparative simulation on MATLAB.Experiments prove that SRMRS has the advantages of low cost,small space occupation and scalability,and SRMRS model effectively measure the impact of various dynamic parameters on the system,the performance of the three algorithms in different tag segments is obvious.(2)This paper analyses the tail ambient intelligence algorithm applied to the single reader movement RFID system.And analyzes the shortcomings of algorithms based on existing algorithms.Two optimization algorithms are proposed:1)A adjustable tail length optimization algorithm(ALT).First,the algorithm reads the new tag tails and stores them in the tail table.Then the tail length adjustment rule is determined by the tail appeared times in a short time.Adjust the length of the tail according to the adjustment rules.The simulation results show that the ALT optimization algorithm improves the slot availability by 33.33%compared with the original algorithm.2)An optimization algorithm with tail continuous identifier as index(TC?).First,k,the times of consecutive occurrences of repeating tails,is counted,k satisfies the Poisson distribution.Secondly,a tail re-recognition cycle is started when k is saturated.The system retrieves the identified tails existing in the signal region from the tail table in B+Tree mode as indexed with the self-growing primary key and stores them in a new table.Finally,the tail with a proportion of F is selected from the new table for tail re-identification.Comparing the performance of the optimization algorithm and the original one by the total identification lap number through simulation experiment,and the results show when the reader finishes the tag recognition task,system efficiency is improved and slot availability improve 25%?50%.