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.

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.

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

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.

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.

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.

Automated Identification Algorithm Using CNN for Computer Vision in Smart Refrigerators

Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge surge of research so as to make smarter refrigerators.According to a survey by the Food and Agriculture Organization of the United Nations(FAO),it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself.Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage.But a major issue is the high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator.To address these issues,this work proposes an automated identification algorithm for computer vision in smart refrigerators using InceptionV3 and MobileNet Convolutional Neural Network(CNN)architectures.The designed module and algorithm have been elaborated in detail and are considerably evaluated for its accuracy using test images on standard fruits and vegetable datasets.A total of eight test cases are considered with accuracy and training time as the performance metric.In the end,real-time testing results are also presented which validates the system’s performance.

Application of PRO-ESPRIT algorithm in identification of surface acoustic wave identification-tags

The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In the measurements based on the frequency domain sampling （FDS）, to expand the range of detection and allow the system work in harsh environments, it is necessary to enhance the identification capability at low SNR. In addition, to identify the tags in real time, it is important to reduce identification time. Therefore, estimation of signal parameters based on the Procrustes rotations via the rotational invariance technique （PRO-ESPRIT） is adopted. Experimental results show that good identification capability is achieved with a relatively faster measurement speed.

Link Budget Design with Performance Evaluation of Tunable Impulse-Based Ultra Wideband to Support the Integration of Wireless Sensing and Identifications Infrastructures

Recently, many studies propose the use of ultra-wideband technology for passive and active radio frequency identification systems as well as for wireless sensor networks due to its numerous advantages. By harvesting these advantages of IR-UWB technology at the physical-layer design, this paper proposes that a cross layer architecture platform can be considered as a good integrator for different wireless short-ranges indoor protocols into a universal smart wireless-tagged architecture with new promising applications in cognitive radio for future applications. Adaptive transmission algorithms have been studied to show the trade-off between different specific QoS requirements, transmission rates and distances at the physical layer level and this type of dynamic optimization and reconfiguration leads to the cross-layer design proposal in the paper. Studies from both theoretical simulation and statistical indoor environments experiments are considered as a proof of concept for the proposed architecture.

一种分布式会议管理系统的设计与实现

基于现代会议管理的需求,设计和实现一种C/S和B/S混合部署的会议管理系统。包括会议管理服务中心和若干个会议现场,会议管理服务中心包括数据服务器、应用服务器、Web服务器、通信网关和出口路由器;会议现场包括若干个便携式电脑、RFID(Radio Frequency Identification)读卡器、二维码阅读器、信息显示发布设备、现场WLAN设备及用户终端。使用RIA(Rich Internet Application)技术优化了B/S界面,应用RFID对会议过程中的细节进行监控,借助SAAS(Software as a Service)模式实现会议管理按需配置和快速部署。该系统显著提高了会议管理效率。

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。

一种用于射频识别阅读器的双频宽带圆极化天线

该文设计了一种紧凑的用作射频识别(RFID)阅读器的双频宽带圆极化天线。天线由弯折处理的矩形贴片、L形贴片和三角形地板构成,通过微带线进行馈电。两个辐射贴片分别独立控制高低两个频段,其轴比带宽也可独立调整,三角形地板可以使横向电流和纵向电流发生变化,从而改变横向电流和纵向电流的比值大小,实现圆极化性能。天线尺寸为0.92λ_(0)×0.92λ_(0)×0.0064λ_(0)(λ_(0)为2.40 GHz时的自由空间波长)。测试结果表明在超高频(UHF)频段该天线实现了49%(0.77~1.27 GHz)的阻抗带宽和46%(0.84~1.34 GHz)的轴比带宽,在无线局域网(WLAN)频段实现了47.5%(1.54~2.50 GHz)的阻抗带宽和24.2%(1.96~2.50 GHz)的轴比带宽,可以完整覆盖UHF和WLAN两个频段,具有良好的辐射特性。与其他双频圆极化天线相比,该天线整体结构紧凑、设计简单、避免了使用复杂的馈电网络,且具有较宽的3 dB轴比带宽。

一种基于相控阵列天线的超高频射频识别相对定位方法

针对已有相对定位方法存在环境依赖程度大、定位精度低等问题,提出一种基于相控阵天线的超高频(UHF)射频识别(RFID)相对定位方法,该方法通过调节相控阵天线的激励参数来改变天线的辐射方向,以获取目标标签的收信场强轮廓,有效降低了系统对环境和场地的依赖程度;同时,提出一种基于轮廓陡峭程度的相对位置估计方法,该方法首先利用轮廓最高点的时间戳信息将目标标签分为两组,然后计算每一组标签的整体轮廓陡峭程度进而估计其相对位置。仿真结果表明:相比于传统相对定位方法,所提相对定位方法能够有效提高定位精度,降低排序偏差;在信噪比为20~30 dB时,性能提高了7.7%~21.6%。上述结果证实了本文方法的有效性。

医疗设备管理系统的构建与实践

目的为助力医院高质量发展,构建一套高效能的医疗装备管理系统。方法使用波特价值链模型梳理医疗设备全生命周期管理的模块需求,运用B/S架构结合射频识别技术,采用JAVA开发工具和Oracle数据库,构建集“购+管+养+控”于一体的医疗设备全生命周期管理系统,实现设备的申请购置、档案管理、维护保养、质量控制等功能,并对其应用效果进行评价。结果系统应用后,设备申请购置的工作效率提升显著,用时缩短了75%;多项设备管理工作平均用时显著缩短,差异有统计学意义(P<0.05);生命支持类设备维修率同比大幅下降;临床对软件的满意度较高,整体满意度在80%以上。结论医疗设备全生命周期管理系统的构建与实践提升了医疗设备管理效率,降低了运维成本,实现了医疗设备规范化、精细化和智能化管理,助力了医院的高质量发展。

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。

基于改进粒子群算法的标签天线结构参数多目标优化设计

为了解决天线设计人员应用电磁仿真软件优化天线结构时存在的优化方向不明确和优化速度慢的问题,文中以干式水表的嵌入式射频识别标签天线设计为例,提出了基于改进粒子群算法的标签天线结构参数多目标寻优方法。首先,根据干式水表产品追溯需求,提出了中心频点尽可能接近理想中心频点、回波损耗尽可能低、带宽尽可能宽、面积尽可能小的四个目标函数。其次,为避免粒子群算法陷入局部最优,采用多维均匀拉丁超立方初始化、Logistic混沌映射非线性变化惯性权重、网格划分变化学习因子、高斯扰动策略等方法对算法进行改进,并应用于标签天线结构参数多目标优化中。最后,进行了实例验证。验证结果表明:利用改进后的粒子群算法得到的标签天线结构参数优化结果可更大程度满足优化目标需求,优化耗时仅为电磁仿真软件的40.1%。

Design and simulation of self-powered radio frequency identification (RFID) tags for mobile temperature monitoring

This paper presents a design for a self-powered radio frequency identification (RFID) tag with a thin film bulk acoustic reso- nating piezoelectric power supply (PPS), which can be used for portable remote temperature monitoring. We call this system a PPS-RFID for short. The RFID systems have been found to have many applications in the internet of things (IOT) in the past decade. But semi-active RFID tags require an onboard battery which limits their applications in many fields. For these reasons, our research focuses on power sources for the RFID tags. This paper emphasizes the circuit design and simulation of PPS. In our tests, 0.283 mW was generated by PPS at 1 Hz vibration by a 650 N impact force. The results showed that the integrated PPS could supply sufficient power for the designed PPS-RFID tag. The PPS-RFID tag can be widely used for temperature monitoring during mobile transport of perishable items such as medicines or food.