Radio Frequency Fingerprint-Based Satellite TT&C Ground Station Identification Method

This study presents a radio frequency(RF)fingerprint identification method combining a convolutional neural network(CNN)and gated recurrent unit(GRU)network to identify measurement and control signals.The proposed algorithm(CNN-GRU)uses a convolutional layer to extract the IQ-related learning timing features.A GRU network extracts timing features at a deeper level before outputting the final identification results.The number of parameters and the algorithm’s complexity are reduced by optimizing the convolutional layer structure and replacing multiple fully-connected layers with gated cyclic units.Simulation experiments show that the algorithm achieves an average identification accuracy of 84.74% at a -10 dB to 20 dB signal-to-noise ratio(SNR)with fewer parameters and less computation than a network model with the same identification rate in a software radio dataset containing multiple USRP X310s from the same manufacturer,with fewer parameters and less computation than a network model with the same identification rate.The algorithm is used to identify measurement and control signals and ensure the security of the measurement and control link with theoretical and engineering applications.

Application of Radio Frequency Identification (RFID) in Dairy Information Management

As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem suggestions for solution according to the practical situation. （RFID） plays an important role in dairy information tracing and culture function extension of managing breeding technology, and finally put forward some

An Overview of Anti-Collision Protocols for Radio Frequency Identification Devices

Radio frequency identification(RFID) is a new type of non-contact automatic identification technology.Due to its low energy consumption,low cost,and its adaptability to harsh environments,it has been applied to many fields.In the RFID systems,data collision is inevitable when the reader sends a communication request and multiple tags respond with simultaneous data transmission.Data collision is prone to causing problems such as:identification delay,spectrum resource waste,a decreased system throughput rate,etc.Therefore,an efficient,stable anti-collision protocol is crucial for RFID systems.This research analysed the current research into RFID anticollision protocols and summarised means for its improvement through the mechanism of implementation of different types anticollision protocols.Finally,a new direction is proposed for the future development of RFID anti-collision protocol systems.

A Modified Split⁃Ring Resonator Antenna for Radio Frequency Identification Tag

A compact antenna formed by three concentric split rings for ultra-high frequency(UHF)radio frequency identification(RFID)tag is proposed in this paper.The antenna is composed of two parts,an outer short-circuited ring modified from a traditional split-ring resonator(SRR)antenna and an inner SRR load,so the antenna can be regarded as a short-circuited ring loaded with SRR.According to the transmission line theory,to conjugate match with the capacitive input-impedance of a tag chip,the length of the short-circuited ring isλg/4 shorter than that of an open-circuited dipole of a traditional SRR antenna,whereλg is the wavelengh of the operating frequency.Hence,the size of the proposed antenna is more compact than that of the traditional SRR antenna.Thereafter,the proposed antenna is simulated and optimized by ANSYS high-frequency structure simulator(HFSS).The impedance,efficiency,and mutual coupling of the fabricated antenna are tested in a reverberation chamber(RC).The results show that the size of the presented antenna is 83%smaller than that of the traditional SRR antenna and the proposed antenna can cover the whole UHF RFID operating frequency band worldwide(840—960 MHz).The measured read range of the tag exhibits maximum values of 45 cm in free space and 37 cm under dense tag environment.

Remanufacturing Closed-Loop Supply Chain Model with Radio Frequency Identification Affecting Recycling Rate

In order to construct a resource-saving and environment- friendly society, the advantages of radio frequency identification （RFID） were considered. And it put forward the idea of introducing RFID in the recycling activities of waste products. Taking into account such elements as the technical level of RFID, cost saving from remanufacturing and the cost of RFID tags, both centralized and decentralized supply chain models with different participants in waste product collection were created, in order to determine the optimal pricing strategy and RFID technical level. In the end, sensitivity analyses were conducted to analyze the impacts of scaling parameter for additional increased recovery rate with RFED on pricing and RFID technology level, and impacts of cost saving on the profits of participants in different remanufacturing closed-loop supply chain models.

RFFsNet-SEI:a multidimensional balanced-RFFs deep neural network framework for specific emitter identification

Existing specific emitter identification(SEI)methods based on hand-crafted features have drawbacks of losing feature information and involving multiple processing stages,which reduce the identification accuracy of emitters and complicate the procedures of identification.In this paper,we propose a deep SEI approach via multidimensional feature extraction for radio frequency fingerprints(RFFs),namely,RFFsNet-SEI.Particularly,we extract multidimensional physical RFFs from the received signal by virtue of variational mode decomposition(VMD)and Hilbert transform(HT).The physical RFFs and I-Q data are formed into the balanced-RFFs,which are then used to train RFFsNet-SEI.As introducing model-aided RFFs into neural network,the hybrid-driven scheme including physical features and I-Q data is constructed.It improves physical interpretability of RFFsNet-SEI.Meanwhile,since RFFsNet-SEI identifies individual of emitters from received raw data in end-to-end,it accelerates SEI implementation and simplifies procedures of identification.Moreover,as the temporal features and spectral features of the received signal are both extracted by RFFsNet-SEI,identification accuracy is improved.Finally,we compare RFFsNet-SEI with the counterparts in terms of identification accuracy,computational complexity,and prediction speed.Experimental results illustrate that the proposed method outperforms the counterparts on the basis of simulation dataset and real dataset collected in the anechoic chamber.

用于油气井RFID扶正器激活的阅读器共形天线设计

基于油气井井下环境的特点,为实现井下扶正器的远程控制,同时改正射频识别(RFID)阅读器天线电磁波强度衰减过大、辐射性能差等缺陷,设计一种共形于井下管道的RFID扶正器阅读器偶极子天线。依据天线设计的基本理论,利用天线弯折技术,将该天线结构设计为倒“U”型,实现与套管相共形;通过仿真扫频分析优化天线参数,分析天线主要结构对性能的影响。结果表明,设计的天线最终的中心频率为860 MHz,在该频率下天线输入端口反射系数为-21.05 dB,增益为2.2 dB,天线尺寸为11 mm×148.44 mm,天线的性能满足设计需求,可用于套管扶正器等井下工具的无线控制。

基于RFID技术的医疗器械信息化追溯系统

为了增强医疗器械系统的整体追溯性能,设计了基于RFID技术的医疗器械信息化追溯系统。在医疗器械信息化追溯系统整体架构下,设计系统硬件部分,包括读写器管理模块、基于RFID技术的数据采集及传输模块、追溯数据处理模块、追溯数据管理模块等,通过上述模块完成对医疗器械信息追溯数据的采集、传输、处理、调用及管理;系统的软件部分,在生产、流通、责任等3个追溯环节下,通过LANDMARC算法和VIRE算法对医疗器械信息追溯,获取追溯标签的最终位置坐标。通过系统CPU内存占用率测试、存储时间测试和追溯效率测试验证了该系统的有效性。

基于RFID的仓储自动化与智能化技术应用

随着全球供应链的不断发展及复杂化,仓储自动化与智能化技术成为提高效率及准确性的关键手段。探讨了射频识别(RFID)在仓储管理中的应用,利用RFID技术可实时追踪商品,减少库存错误,降低人工操作需求,提高整体物流速度。将传统的条形码系统与RFID系统进行对比,揭示RFID在准确性、可靠性及数据收集速度等方面的优势,为未来的仓储自动化与智能化发展提供参考。

基于RFID技术的消毒供应追溯系统的应用研究

文章深入研究了基于射频识别(radio frequency identification,RFID)技术的消毒供应追溯系统的应用,探讨了RFID技术在医疗器械管理中的应用潜力和实际效果。文章详细分析了RFID技术在提高消毒供应追溯系统效率和准确性方面的优势,同时指出了在实际应用过程中所面临的挑战和解决方案。通过本医院系统的应用和实施,展示了RFID技术在优化医疗资源管理、提升医疗服务质量以及保障患者安全方面的重要作用。

基于STC8H的USB接口RFID读卡器设计

设计了一种具有HID接口的RFID读卡器,该读卡器采用带硬件USB接口的STC8H单片机作为主控,采用多协议射频芯片FM1722作为读卡芯片,读卡器具有接口方便、读写速度快、性价比高、支持卡类型多等优点,可以用在物流、交通、身份识别、安全控制等领域。

基于RFID技术的公共交通自动到站播报系统设计

随着城市公共交通的迅速发展,如何提升乘客乘车的体验与提高交通系统的管理效率变得愈发重要。本文研究基于射频识别技术(RFID),设计智能化的公共交通自动到站播报系统,经过需求分析、架构设计及硬件和软件实现等步骤,助力创建出一个高效可靠的自动到站播报系统。该系统能够准确实时定位车辆并触发到站播报,让乘客出行变得更加便捷,并有利于将整个公共交通体系推向更高程度的智能化阶段。

基于方形螺旋谐振器的紧凑型RFID标签天线

设计了一种小型化超高频(UHF,ultra-high frequency)射频识别(RFID,radio frequency identification)标签天线。该天线由内外两个方形螺旋谐振器短接构成,通过改变外圈螺旋谐振器的边长和内外圈螺旋谐振器的间距,可以有效调节标签天线的谐振频率。仿真结果表明,标签天线阻抗匹配良好,频带范围覆盖整个超高频频段(840~960 MHz),总尺寸为7.60 mm×7.60 mm×0.05 mm,比传统螺旋谐振器(SR,spiral resonator)天线小96%。测试结果表明,在4 W有效全向辐射功率条件下,标签天线在910 MHz处读取距离达到最大。所提小型化超高频射频识别标签天线具有尺寸小、频带宽、成本低和易于批量制作的特点,适用于对尺寸要求较小的应用环境。

RFID技术在食品智能包装和供应链追溯中的应用研究

目的介绍RFID技术,综述其在智能包装、食品供应链追溯的应用进展,以期为RFID技术的发展提供一定的理论基础。方法阐述RFID系统的组成、分类、工作原理及该技术的优点;分析RFID技术在监测食品包装内温度、湿度、pH、气体含量等参数的应用潜力;综述RFID技术在整个食品供应链(生产、加工、储运和销售环节)中的追溯进展;讨论目前RFID技术在实际应用中面临的问题和今后的发展方向。结论通过全面综述RFID技术在智能包装、食品溯源等方面的应用,表明RFID技术在食品领域具有广泛的应用前景,这对食品质量控制具有重要的意义。

Recovery of Collided RFID Tags With Frequency Drift on Physical Layer

In a passive ultra-high frequency(UHF)radio frequency identification(RFID)system,the recovery of collided tag signals on a physical layer can enhance identification efficiency.However,frequency drift is very common in UHF RFID systems,and will have an influence on the recovery on the physical layer.To address the problem of recovery with the frequency drift,this paper adopts a radial basis function(RBF)network to separate the collision signals,and decode the signals via FM0 to recovery collided RFID tags.Numerical results show that the method in this paper has better performance of symbol error rate(SER)and separation efficiency compared to conventional methods when frequency drift occurs.

集成双频无源RFID传感器标签设计

针对超高频和高频RFID传感器由于各自测量距离和使用便捷性而导致应用场合的局限,提出一种集成超高频和高频的双频无源RFID传感器标签设计方法。首先,集成超高频和高频射频供电和数据收发模块,达到超高频和高频双频读写目的;其次,为提高双频RFID传感器标签在超高频模式下的读取距离,采用电荷泵对射频收发芯片输出电压进行升压管理以延长放电时间;然后,为增强传感器标签的通用性,将测量数据集成到高频NDEF消息和超高频用户数据段中。根据以上方法,设计了双频无源RFID温湿度传感器标签。同时搭建了实验平台对电荷泵提升读取距离的可行性和传感器标签功能进行了实验验证。实验结果表明:该传感器标签可以同时支持超高频和高频2种读取模式;使用电荷泵升压能量管理有效提升了读取距离;可通过支持EPCC1G2协议的通用超高频读写器和NFC手机方便地获取传感器测量数据。

Capture-aware Bayesian RFID Tag Estimate for Large-scale Identification

Dynamic framed slotted Aloha algorithm is one of popular passive radio frequency identification(RFID) tag anticollision algorithms. In the algorithm, a frame length requires dynamical adjustment to achieve higher identification efficiency.Generally, the adjustment of the frame length is not only related to the number of tags, but also to the occurrence probability of capture effect. Existing algorithms could estimate both the number of tags and the probability of capture effect. Under large-scale RFID tag identification, however, the number of tags would be much larger than an initial frame length. In this scenario, the existing algorithm's estimation errors would substantially increase. In this paper, we propose a novel algorithm called capture-aware Bayesian estimate, which adopts Bayesian rules to accurately estimate the number and the probability simultaneously. From numerical results, the proposed algorithm adapts well to the large-scale RFID tag identification. It has lower estimation errors than the existing algorithms. Further,the identification efficiency from the proposed estimate is also higher than the existing algorithms.

Design and Implementation of a Low-Power Active RFID for Container Tracking at 2.4 GHz Frequency

In this paper a new active RFID system at 2.45 GHz based on the low-power system-on-chip CC2530 RF transceiver is designed and implemented. Only by using of an integrated multi-channel fast chip, both the MCU and RF operations are done which makes the RFID more reliable and reduces the complexity of the hardware and cost, vividly. This RFID system utilizes the Zig-Bee IEEE 802.15.4 standard in the ISM band. A lot amount of energy is restored by setting Tags in the sleep mode in the most of times. The maximum transmission range of 80 m at the output power of 4.5 dBm is obtained. The main application of this system is for the container identification with precise operation and high accuracy. An active Tag with unique ID is mounted on each vehicle. By enabling the AUTOCRC error detection possibility, minor errors are detected in the received frames. Receiver sensitivity of –97 dBm and current consumption of 1 μA in the sleep mode and 29.6 mA in the active mode are reported.

基于RFID的人体姿态识别方法研究

人体姿态感知是未来智能护理场景的主要挑战之一。然而,视觉技术会涉及遮挡、光线条件、侵犯隐私等问题;可穿戴运动跟踪设备会增加人体负担,降低舒适性。针对以上问题,提出了一种基于射频识别(RFID)的方法进行全肢体姿态估计,能够有效克服遮挡、穿戴舒适性差等问题。首先基于相位差信息提出了一种细粒度肢体运动模型,通过构建似然函数来进行人体关节角度估计;引入正运动学构建多肢体联合运动模型,结合双天线融合算法进行三维关节角度估计;最后结合人体骨骼模型与肢体关节角度来重建人体姿态。实验结果以Kinect 2.0为标准,测得的四肢平均关节角度误差约为6°,平均关节位置误差约为4cm,表明该系统可以有效地实时监测全肢体姿态。

基于RFID的笼内小鼠定位跟踪系统设计

常见的定位技术用于笼内小鼠跟踪准确度不高。为提高笼内小鼠定位准确性,提出了一种基于射频识别(RFID)技术的笼内小鼠定位跟踪和行为分析系统,通过放置在饲养笼下方的RFID读写器天线阵列板实现定位跟踪,上位机软件可实时显示小鼠的活动轨迹图以便科研人员对小鼠进行行为分析。通过模拟实验和生物实验,该系统可准确定位4×6阵列中小鼠位置,定位准确率可达95%以上,其中,组成阵列的单元格尺寸仅为45 mm×45 mm。