RFID协议一致性测试系统中标签相位和幅度的计算算法

Na Wang, Yingge Xu, Yajun Zhang, Meng Liu, Daxue Shen, Hongjun Wang
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引用次数: 1

摘要

如今,RFID(无线射频识别)技术被广泛应用于物流管理、收费系统以及授权管理等领域。但在RFID系统中,读写器的性能和标签的性能是影响RFID系统性能的最大因素,因此本文主要研究如何利用对信号影响明显的CFO来计算标签的相位和幅度。本文提出了一种基于RFID协议一致性测试系统和RFID信号分析系统的降低CFO和载波频率漂移影响的算法。我们用统计的思想和分段线性拟合来寻找信号的变化来解决CFO问题。难点在于如何精确定位变化率变化的位置以及信号的开始和结束位置。利用标签相位变化率和标签振幅变化率对标签信号进行分离校正,利用聚类得到信号中心点计算标签相位。该算法已在我们的系统中得到应用。在本文中,我们完成了信号的分割和分析。为了更准确地分离标签信号和读取器信号,我们先对信号进行滤波,然后使用状态转移模型。我们首先用简单聚类粗略计算载波的值。然后我们开始研究状态转换模型。最后,我们得到了读取器信号和标签信号的正确位置。介绍了18000-6C标签信号和18000-6B标签信号的相位和幅度的获取方法。分析了CFO和频率漂移对18000-6c信号和18000-6B信号的影响,提出了针对不同协议的算法。我们得到18000-6b的IQ信号大致是周期性的,但周期有一点波动。我们用统计学的思想准确地找到周期,用拟合曲线来拟合相位的变化。我们得到18000-6C信号的标签相位在一个符号中线性增加。所以对于18000-6c的信号,我们对整个标签信号采用分段线性拟合而不是线性回归。在我们修改相位之后我们就得到了正确的标签振幅和相位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An algorithm to calculate phase and amplitude of tag on RFID protocol conformance test system
Nowadays, RFID (Radio Frequency Identification) technology is widely used in logistics management, tolling system as well as authorization management. But either the performance of reader or tag is the largest influence factor in RFID systems compared with other components, so this paper mainly works on how to calculate tag phase and amplitude by signal with CFO that have an obvious influence on signal. This paper propose, an algorithm reducing influence CFO and carrier frequency drift have based on RFID protocol conformance test system and RFID signal analysis system. We find the change of signal with statistical idea and piecewise linear fitting to solve CFO. The difficulty is how to pinpoint location where rate of change changes and locate the start and end of signal. We use rate of change of tag phase and tag amplitude to separate tag signal to correct it, and we use cluster to get center points of signal to calculate tag phase. This algorithm has been used in our system. In this paper, we finished segmentation of signal and analysis of signal. To separate tag signal and reader signal more accurately, we filter signal firstly and then use state transition model. We calculate the value of carrier roughly with simple cluster firstly. Then we start work with state transition model. Finally, we get right location of reader signal and tag signal. And we introduce how to get the phase and amplitude of 18000-6C tag signal and 18000-6B tag signal. We analysis the influence on 18000-6c signal and 18000-6B that CFO and frequency drift have, and propose algorithms for different protocol. We get that 18000-6b IQ signals approximately periodic, but period is a little fluctuate. We use statistical idea to find the period accurately and use fitting curve to fit the change of phase. We get that tag-phase of 18000-6C signal increased linearly in a symbol. So with 18000-6c signal, we adopt piecewise linear fitting not linear regression in a whole of tag signal. After we modify the phase and then we get the correct tag amplitude and tag phase.
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