Search Results (6)

Although RFID(radio frequency identification) tags do not require a direct line of sight, their operational range is often characterized as being limited. Indeed, in the case of passive RFID tags, the interrogating signal from the transmitter needs to reach the tag’s radio transponder and trigger a nearly omnidirectional scattered signal to be harvested by the receiver. This two-way (from Tx to the tag and back to Rx) channel exhibits increased attenuation not only due to the doubled distance (in case Tx and Rx are collocated) but also to the uncontrolled (i.e., unfocused) backscattering. In the work at hand, we propose a way to control the backscattered radiation and focus the produced beam towards the direction of the reader (the Tx-Rx device). Indeed, one can utilize the concept of retrodirective arrays to immediately control the direction of departure of the backscatter link, maximizing the scattered power towards the reader and thus delivering an increase in the operational range of the tag. This of course means that in this case, the tag should be equipped with a minimum of two element radiators. Thus, retrodirective RFID array tags are introduced in the current work to increase the operating range with minimal costs and levels of complexity since 90° hybrids are used to achieve proper backscattering. To evaluate the proposed passive tag array, performance aspects are addressed. Specifically, we examine the Bit Error Rate with respect to the Signal to Noise Ratio for the retrodirective tag, the one antenna, the broadside, and the spatial diversity array. The results prove that the proposed tag allows for a significant increase in the operational range. Full article

Chipless RFID tags have attractive low-cost advantages. However, traditional RFID anti-collision algorithms cannot be applied due to a lack of computing and processing capabilities. Problems with multitag detection must be solved to commercialize chipless RFID tags. In this paper, an innovative method for frequency-domain chipless RFID tag detection is proposed. The tags’ scattered signals are processed via wavelet analysis, and a time–frequency plot that can read the code is obtained. When the distance between tags is too close to distinguish in the time–frequency plot, independent component analysis is used to separate individual scattered signals from mixed echo signals; then, the code is read by means of wavelet analysis. To validate the proposed method, C-shaped frequency-domain chipless RFID tag models and a multitag detection simulation scenario were constructed in selected software. The short-time matrix pencil method (STMPM), short-time Fourier transform (STFT), and the proposed method were compared. When the tag spacing is 0.05 m, the code can be read successfully. Compared with the STMPM, the proposed method greatly reduces the computational quantity and shortens the reading time. Furthermore, adjustment of the window width and search step parameters is avoided. Full article

RFID-based technology innovated a new field of wireless sensing, which has been applied in posture recognition, object localization, and the other sensing fields. Due to the presence of a Fresnel zone around a magnetic field when the RFID-based system is working, the signal undergoes significant changes when an object moves through two or more different Fresnel zones. Therefore, the moving object can be sensed more easily, and most of the sensing applications required the tag to be attached to the moving object for better sensing, significantly limiting their applications. The existing technologies to detect static objects in agricultural settings are mainly based on X-ray or high-power radar, which are costly and bulky, making them difficult to deploy on a large scale. It is a challenging task to sense a static target without a tag attached in NLOS (non-line-of-sight) detection with low cost. We utilized RFID technologies to sense the static foreign objects in agricultural products, and take metal, rock, rubber, and clod as sensing targets that are common in agriculture. By deploying tag matrices to create a sensing region, we observed the signal variations before and after the appearance of the targets in this sensing region, and determined the targets’ positions and their types. Here, we buried the targets in the media of seedless cotton and wheat, and detected them using a non-contact method. Research has illustrated that, by deploying appropriate tag matrices and adjusting the angle of a single RFID antenna, the matrices’ signals are sensitive to the static targets’ positions and their properties, i.e., matrices’ signals vary with different targets and their positions. Specifically, we achieved a 100% success rate in locating metallic targets, while the success rate for clods was the lowest at 86%. We achieved a 100% recognition rate for the types of all the four objects. Full article

With radio frequency identification (RFID) becoming a popular wireless technology, more and more relevant applications are emerging. Therefore, anti-collision algorithms, which determine the time to tag identification and the accuracy of identification, have become very important in RFID systems. This paper presents the algorithms of ALOHA for randomness, the binary tree algorithm for determinism, and a hybrid anti-collision algorithm that combines these two algorithms. To compensate for the low throughput of traditional algorithms, RFID anti-collision algorithms based on blind source separation (BSS) are described, as the tag signals of RFID systems conform to the basic assumptions of the independent component analysis (ICA) algorithm. In the determined case, the ICA algorithm-based RFID anti-collision method is described. In the under-determined case, a combination of tag grouping with a blind separation algorithm and constrained non-negative matrix factorization (NMF) is used to separate the multi-tag mixing problem. Since the estimation of tag or frame length is the main step to solve the RFID anti-collision problem, this paper introduces an anti-collision algorithm based on machine learning to estimate the number of tags. Full article

Radio frequency identification (RFID) is a kind of non-contact automatic identification technology. The Internet of Vehicles (IoV) is a derivative of the Internet of Things (IoT), and RFID technology has become one of the key technologies of IoV. Due to the open wireless communication environment in RFID system, the RFID system is easy to be exposed to various malicious attacks, which may result in privacy disclosure. The provision of privacy protection for users is a prerequisite for the wide acceptance of the IoV. In this paper, we discuss the privacy problem of the RFID system in the IoV and present a lightweight RFID authentication scheme based on permutation matrix encryption, which can resist some typical attacks and ensure the user’s personal privacy and location privacy. The fast certification speed of the scheme and the low cost of the tag is in line with the high-speed certification requirement in the Internet of vehicles. In this thesis, the specific application scenarios of the proposed RFID authentication scheme in the IoV is also discussed. Full article

In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and, thus, enhance the identification efficiency of the RFID system. For the recovery on the PHY layer, channel estimation is a critical issue. Good channel estimation will help to recover the collided signals. Existing channel estimates work well for two collided tags. When the number of collided tags is beyond two, however, the existing estimates have more estimation errors. In this paper, we propose a novel channel estimate for the UHF RFID system. It adopts an orthogonal matrix based on the information of preambles which is known for a reader and applies a minimum-mean-square-error (MMSE) criterion to estimate channels. From the estimated channel, we could accurately separate the collided signals and recover them. By means of numerical results, we show that the proposed estimate has lower estimation errors and higher separation efficiency than the existing estimates. Full article