Research On Key Technology Of RFID Tag Anti-collision

Radio frequency identification technology(RFID),as a key technology for collecting data information at the perception layer of the Internet of Things,has the advantages of fast reading,multi-target recognition,low cost,high data security,and non-line-of-sight.When multiple tags send information to a reader at the same time,collisions occur between tags due to the presence of co-channel interference,which greatly reduces the system throughput.Therefore,this paper studies the key technologies of tag anti-collision from two perspectives: tag number estimation and tag identification.Aiming at the problems of large estimation error,prolonged recognition time and high time complexity in existing tag quantity estimation algorithms in RFID systems,Twice Tags Number Estimation algorithm based on Gaussian fitting and Chebyshev inequality(TLNEGC)is proposed.First,establish a collision model based on the relationship between the collision factor and the collision time slot ratio,and use the Gaussian function to fit the discrete data points in the collision model to obtain the Gaussian estimation model;then use the Gaussian estimation model to estimate the number of tags for the first time,according to the initial estimation As a result,it is judged whether a second estimation is required.The second estimation is to use Chebyshev's inequality to search the estimation interval twice to obtain the best estimation value.MATLAB simulation analysis shows that the average estimation error and total time consumption of the TLNEGC algorithm are significantly lower than the existing high-precision tag estimation algorithms,and it has lower time complexity and higher stability.Aiming at the high latency and low throughput problems of existing Tag recognition systems using ALOHA algorithm or TREE algorithm or a combination of the two algorithms,Tag Recognition Algorithm based on Tag Prefix Pruning(LRAPP).The LRAPP algorithm includes two sub-algorithms of slot prefix matching and prefix pruning estimation.Slot prefix matching means that the tag judges whether its prefix matches the slot prefix,and if it matches,it responds to the reader;tag pruning estimation is to cut the slot corresponding to the non-collision slot prefix first,and then use the tag number estimation algorithm to calculate the collision slot The number of tags.MATLAB simulation analysis shows that the total time slot consumption and collision time slots of the LRAPP algorithm are significantly lower than the existing tag recognition algorithms.