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 su...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展开更多
目的确保物品包装上的超高频射频识别(Radio Frequency Identification,RFID)标签一致性关键指标符合相关标准,解决现有文献对一致性关键指标阐述不全面的问题,基于ISO/IEC 18000-63和ISO/IEC 18047-63对一致性关键指标的测试方法展开...目的确保物品包装上的超高频射频识别(Radio Frequency Identification,RFID)标签一致性关键指标符合相关标准,解决现有文献对一致性关键指标阐述不全面的问题,基于ISO/IEC 18000-63和ISO/IEC 18047-63对一致性关键指标的测试方法展开研究。方法在对现有一致性测试方法进行研究阐述的基础上,改进了状态跳转和截断响应的测试方法,提升了测试准确性;设计了一种时隙计数器测试方法,该方法通过改变Q值和重复发送QueryRep命令,验证时隙计数器在非0到0的变化过程中,标签有且仅有一次响应,从而避免出现多个标签同时应答的现象。结果应用改进及新设计的测试方法对指定标签进行测试,结果符合标准。结论较为全面地实现了对RFID标签的客观验证和有效评估,对提升RFID标签在实际应用中的可靠性具有重要意义。展开更多
研究设计并实现了一种基于U型谐振单元的无芯片射频识别(radio frequency identification,RFID)技术湿度传感器,该传感器结合Vivaldi宽频段天线,构建了一套无线无源的湿度传感系统,可实现对环境湿度的实时监测。无芯片RFID湿度传感器由8...研究设计并实现了一种基于U型谐振单元的无芯片射频识别(radio frequency identification,RFID)技术湿度传感器,该传感器结合Vivaldi宽频段天线,构建了一套无线无源的湿度传感系统,可实现对环境湿度的实时监测。无芯片RFID湿度传感器由8个U型谐振单元和1条与之耦合的微带线构成。在该设计中,两侧对称的谐振单元用于校准环境温度对湿度传感器的影响,其中1个单元由聚乙烯醇(polyvinyl alcohol,PVA)湿敏材料覆盖;中间6个U型单元用于RFID湿度传感器的ID信息编码。此外,本工作采用矩形环开槽技术优化了宽频带Vivaldi天线,并结合传感器实现了无线无源湿度传感。有线实验数据显示,在57%RH~71%RH的相对湿度范围内,产生了118 MHz的频率偏移,平均灵敏度为8.4 MHz/%RH。无线实验结果显示,在49%RH~70%RH的相对湿度范围内,产生了103 MHz的频率偏移,平均灵敏度为4.9 MHz/%RH。实验结果表明该无线无源湿度传感装置具有较高的检测灵敏度,可为无线无源湿度检测提供重要的解决方案。展开更多
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 emi...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.展开更多
基金Supported by the Project of the National "948" (2006-Z12)
文摘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
文摘目的确保物品包装上的超高频射频识别(Radio Frequency Identification,RFID)标签一致性关键指标符合相关标准,解决现有文献对一致性关键指标阐述不全面的问题,基于ISO/IEC 18000-63和ISO/IEC 18047-63对一致性关键指标的测试方法展开研究。方法在对现有一致性测试方法进行研究阐述的基础上,改进了状态跳转和截断响应的测试方法,提升了测试准确性;设计了一种时隙计数器测试方法,该方法通过改变Q值和重复发送QueryRep命令,验证时隙计数器在非0到0的变化过程中,标签有且仅有一次响应,从而避免出现多个标签同时应答的现象。结果应用改进及新设计的测试方法对指定标签进行测试,结果符合标准。结论较为全面地实现了对RFID标签的客观验证和有效评估,对提升RFID标签在实际应用中的可靠性具有重要意义。
基金supported by the National Natural Science Foundation of China(62061003)Sichuan Science and Technology Program(2021YFG0192)the Research Foundation of the Civil Aviation Flight University of China(ZJ2020-04,J2020-033)。
文摘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.
