【作者】 郭志涛；

【导师】 顾军华；

【作者基本信息】 河北工业大学 ， 电气工程， 2011， 博士

【摘要】 射频识别(Radio Frequency Identification,RFID)技术是一种新型的自动识别技术,近几年发展十分迅速,在很多领域获得了广泛应用。但在RFID技术应用推广过程中,仍存在超高频RFID读写器微带天线结构设计困难,谐振频率难以确定,以及多个标签同时进入读写区引发标签碰撞而无法识别等问题,这些问题限制了RFID技术的深入应用。本文在论述RFID技术研究意义、基本理论的基础上重点分析了智能算法在微带天线建模中的应用以及标签防碰撞问题的解决方法,最后对超高频RFID技术在公交调度系统中的应用方案进行了设计。首先,对RFID阅读器微带天线建模中智能算法进行了研究,提出采用改进粒子群算法训练神经网络建立天线结构与天线谐振频率的模型。天线的结构与性能是一个比较复杂的非线性系统,系统状态复杂,难以用数学方法准确建模。本文分别采用了基本BP算法、GA算法和改进PSO算法训练神经网络实现频率模型,依次解决了网络过早收敛、网络精度低等问题。实验结果表明,采用粒子群优化神经网络能够建立准确、完备的微带天线谐振频率与结构之间的模型,能够实现天线快速设计。其次,对RFID系统中多标签碰撞问题进行研究,提出标签估算的快速方法以及基于预处理机制的逆向二进制防碰撞算法。本文在实验的基础上建立碰撞概率与平均碰撞标签数的曲线关系,并采用折线拟合的方法进行标签估算,以提高识别速度;通过分析不同帧长系统效率的关系,改进了帧长度的调整方法;在二进制搜索算法中融入预处理机制,减少读写器与标签的通信数据量。通过仿真实验证明了改进后的方法能够有效减少识别时间,提高识别效率。最后,结合当前公共交通的特点,提出一种新颖的基于超高频RFID技术的智能公交调度系统设计方案,并研制了高频13.56MHz和超高频915MHz的双频点RFID读写器。实际测试表明设计双频点RFID读写器能够同时实现高频和超高频的读写卡功能,设计的微带天线谐振频率符合要求,且改进后的标签防碰撞算法识别速度更快。更多还原

【Abstract】 RFID (Radio Frequency Identification, RFID) technology is a new type of automatic identification technology. It developed very rapidly in recent years, and has been widely used in many applications.But there are some key issues in RFID techology promotion process, such as it is difficult to determine the resonant frequency in design of UHF RFID reader microstrip antenna, and it can not identify the multiple collision tags when they simultaneously come into the reader’s area.These problems limited the further application of RFID technology.This paper discussed the significance of RFID technology and the basic theory, and analysised the intelligent algorithm’s application in the modeling of microstrip antenna. Furthermore the tag anti-collision solution technology has been illustrated. Finally, the public transport scheduling system based on UHF RFID technology has been designed.Firstly, the intelligent algorithm in modeling of microstrip antenna RFID reader has been studied and a modified particle swarm algorithm trained neural network structure used in the antenna resonant frequency of the antenna model has been proposed.The structure and properties of the antenna is a much more complicated nonlinear system which is hard to model mathematically accurately. The basic BP algorithm, GA algorithm and the improved PSO algorithm to train neural network frequency model has been researched in order to solve premature convergence of the network, the network and low accuracy problem.The experiment results showed that PSO neural network could establish an accurate, complete modele between the resonant frequency and structure of microstrip antenna,which could achieve the design of the reader antenna rapidly.Secondly, multi-tags collision problem had been studied, and a quick method to estimate the proposed tags’ number and a novel anti-collision algorithm based on reverse mechanism had been proposed.In this paper, the curve between the number of collisions and the average collision probability has been estimated which was based on the experiment data. The curve was replaced by the simplified line, and then the recognition speed had been increased. By analyzing the relationship between the different frame sizes, the frame length adjustment method was improved.In the binary search algorithm, the pretreatment mechanism had been proposed to reduce the communication reader and tag data. The simulation results demonstrated the improved method could effectively reduce the recognition time and improve recognition efficiency.Finally, combining the characteristics of public transport, a novel intelligent transportation scheduling system based on ultra-high frequency RFID technology had been proposed. And a dual-frequency RFID reader which has 13.56MHz and UHF 915MHz was designed and realized. Actual tests showed that the dual frequency points RFID readers could simultaneously achieve function of read-write card function both in high frequency and ultra high frequency, and resonant frequency of microstrip antenna could meet the real requirements.At the same time, and improved identification tag anti-collision algorithm is faster.更多还原