ABSTRACT
This paper details the design and implementation of a harmonic frequency-modulated continuous-wave (FMCW) radar system, specialized in detecting harmonic tags and achieving precise range estimation. Operating within the 2.4-2.5 GHz frequency range for the forward channel and 4.8-5.0 GHz for the backward channel, this study delves into the various challenges faced during the system's realization. These challenges include selecting appropriate components, calibrating the system, processing signals, and integrating the system components. In addition, we introduce a single-layer passive harmonic tag, developed specifically for assessing the system, and provide an in-depth theoretical analysis and simulation results. Notably, the system is characterized by its low power consumption, making it particularly suitable for short-range applications. The system's efficacy is further validated through experimental evaluations in a real-world indoor environment across multiple tag positions. Our measurements underscore the system's robust ranging accuracy and its ability to mitigate self-interference, showcasing its significant potential for applications in harmonic tag detection and ranging.
ABSTRACT
Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This extensive mathematical model developed for linear chipless RFID systems in clutter scenarios holds the potential to greatly assist researchers in their exploration of RCS-based tags. By relying solely on simulations, this model provides a tool to effectively analyze and understand RCS-based tags, ultimately simplifying the process of generating more authentic tag designs. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.
ABSTRACT
Synthetic aperture radar (SAR) at the terahertz (THz) spectrum has emerging short-range applications. In comparison to the microwave spectrum, the THz spectrum is limited in propagation range but benefits from high spatial resolution. The THz SAR is of significant interest for several applications which necessitate the mapping of indoor environments to support various endeavors such as rescue missions, map-assisted wireless communications, and household robotics. This paper addresses the augmentation of the high-resolution indoor mapped environment for object recognition, which includes detection, localization, and classification. Indoor object recognition is currently dominated by the usage of optical and infrared (IR) systems. However, it is not widely explored by radar technologies due to the limited spatial resolution at the most commonly used microwave frequencies. However, the THz spectrum provides a new paradigm of possible adaptation of object recognition in the radar domain by providing image quality in good compliance to optical/IR systems. In this paper, a multi-object indoor environment is foremost mapped at the THz spectrum ranging from 325 to 500 GHz in order to investigate the imaging in highly scattered environments and accordingly create a foundation for detection, localization, and classification. Furthermore, the extraction and clustering of features of the mapped environment are conducted for object detection and localization. Finally, the classification of detected objects is addressed with a supervised machine learning-based support vector machine (SVM) model.
ABSTRACT
This paper focuses on the frequency coded chipless Radio Frequency Identification (RFID) wherein the tag's information bits are physically encoded by the resonators' notch position which has an effect on the frequency spectrum of the backscattered or retransmitted signal of the tag. In this regard, the notch analytical model is developed to consider the notch position and quality factor. Besides, the radar cross section (RCS) mathematical representation of the tag is introduced to consider the incident wave's polarization and orientation angles. Hence, the influences of the incident wave's orientation and polarization mismatches on the detection performance are quantified. After that, the tag measurement errors and limitations are comprehensively explained. Therefore, approaches to measureing RCS- and retransmission-based tags are introduced. Furthermore, the maximum reading range is theoretically calculated and practically verified considering the Federal Communications Commission (FCC) Ultra Wideband (UWB) regulations. In all simulations and experiments conducted, a mono-static configuration is considered, in which one antenna is utilized for transmission and reception.
