418 research outputs found

    Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool

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    Accelerated by the increasing attention drawn by 5G, 6G, and Internet of Things applications, communication and sensing technologies have rapidly evolved from millimeter-wave (mmWave) to terahertz (THz) in recent years. Enabled by significant advancements in electromagnetic (EM) hardware, mmWave and THz frequency regimes spanning 30 GHz to 300 GHz and 300 GHz to 3000 GHz, respectively, can be employed for a host of applications. The main feature of THz systems is high-bandwidth transmission, enabling ultra-high-resolution imaging and high-throughput communications; however, challenges in both the hardware and algorithmic arenas remain for the ubiquitous adoption of THz technology. Spectra comprising mmWave and THz frequencies are well-suited for synthetic aperture radar (SAR) imaging at sub-millimeter resolutions for a wide spectrum of tasks like material characterization and nondestructive testing (NDT). This article provides a tutorial review of systems and algorithms for THz SAR in the near-field with an emphasis on emerging algorithms that combine signal processing and machine learning techniques. As part of this study, an overview of classical and data-driven THz SAR algorithms is provided, focusing on object detection for security applications and SAR image super-resolution. We also discuss relevant issues, challenges, and future research directions for emerging algorithms and THz SAR, including standardization of system and algorithm benchmarking, adoption of state-of-the-art deep learning techniques, signal processing-optimized machine learning, and hybrid data-driven signal processing algorithms...Comment: Submitted to Proceedings of IEE

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Autonomous Radar-based Gait Monitoring System

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    Features related to gait are fundamental metrics of human motion [1]. Human gait has been shown to be a valuable and feasible clinical marker to determine the risk of physical and mental functional decline [2], [3]. Technologies that detect changes in people’s gait patterns, especially older adults, could support the detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. Gait assessment has the potential to be leveraged as a clinical measurement as it is not limited to a specific health care discipline and is a consistent and sensitive test [4]. A wireless technology that uses electromagnetic waves (i.e., radar) to continually measure gait parameters at home or in a hospital without a clinician’s participation has been proposed as a suitable solution [3], [5]. This approach is based on the interaction between electromagnetic waves with humans and how their bodies impact the surrounding and scattered wireless signals. Since this approach uses wireless waves, people do not need to wear or carry a device on their bodies. Additionally, an electromagnetic wave wireless sensor has no privacy issues because there is no video-based camera. This thesis presents the design and testing of a radar-based contactless system that can monitor people’s gait patterns and recognize their activities in a range of indoor environments frequently and accurately. In this thesis, the use of commercially available radars for gait monitoring is investigated, which offers opportunities to implement unobtrusive and contactless gait monitoring and activity recognition. A novel fast and easy-to-implement gait extraction algorithm that enables an individual’s spatiotemporal gait parameter extraction at each gait cycle using a single FMCW (Frequency Modulated Continuous Wave) radar is proposed. The proposed system detects changes in gait that may be the signs of changes in mobility, cognition, and frailty, particularly for older adults in individual’s homes, retirement homes and long-term care facilities retirement homes. One of the straightforward applications for gait monitoring using radars is in corridors and hallways, which are commonly available in most residential homes, retirement, and long-term care homes. However, walls in the hallway have a strong “clutter” impact, creating multipath due to the wide beam of commercially available radar antennas. The multipath reflections could result in an inaccurate gait measurement because gait extraction algorithms employ the assumption that the maximum reflected signals come from the torso of the walking person (rather than indirect reflections or multipath) [6]. To address the challenges of hallway gait monitoring, two approaches were used: (1) a novel signal processing method and (2) modifying the radar antenna using a hyperbolic lens. For the first approach, a novel algorithm based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method is proposed. This proposed algorithm could be paired with any type of multiple-input multiple-output (MIMO) or single-input multiple-output (SIMO) FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. The algorithm functionality was validated by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a hallway. The preliminary results demonstrate the promising potential of the algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments. For the second approach, an in-package hyperbola-based lens antenna was designed that can be integrated with a radar module package empowered by the fast and easy-to-implement gait extraction method. The system functionality was successfully validated by capturing the spatiotemporal gait values of people walking in a hallway filled with metallic cabinets. The results achieved in this work pave the way to explore the use of stand-alone radar-based sensors in long hallways for day-to-day long-term monitoring of gait parameters of older adults or other populations. The possibility of the coexistence of multiple walking subjects is high, especially in long-term care facilities where other people, including older adults, might need assistance during walking. GaitRite and wearables are not able to assess multiple people’s gait at the same time using only one device [7], [8]. In this thesis, a novel radar-based algorithm is proposed that is capable of tracking multiple people or extracting walking speed of a participant with the coexistence of other people. To address the problem of tracking and monitoring multiple walking people in a cluttered environment, a novel iterative framework based on unsupervised learning and advanced signal processing was developed and tested to analyze the reflected radio signals and extract walking movements and trajectories in a hallway environment. Advanced algorithms were developed to remove multipath effects or ghosts created due to the interaction between walking subjects and stationary objects, to identify and separate reflected signals of two participants walking at a close distance, and to track multiple subjects over time. This method allows the extraction of walking speed in multiple closely-spaced subjects simultaneously, which is distinct from previous approaches where the speed of only one subject was obtained. The proposed multiple-people gait monitoring was assessed with 22 participants who participated in a bedrest (BR) study conducted at McGill University Health Centre (MUHC). The system functionality also was assessed for in-home applications. In this regard, a cloud-based system is proposed for non-contact, real-time recognition and monitoring of physical activities and walking periods within a domestic environment. The proposed system employs standalone Internet of Things (IoT)-based millimeter wave radar devices and deep learning models to enable autonomous, free-living activity recognition and gait analysis. Range-Doppler maps generated from a dataset of real-life in-home activities are used to train deep learning models. The performance of several deep learning models was evaluated based on accuracy and prediction time, with the gated recurrent network (GRU) model selected for real-time deployment due to its balance of speed and accuracy compared to 2D Convolutional Neural Network Long Short-Term Memory (2D-CNNLSTM) and Long Short-Term Memory (LSTM) models. In addition to recognizing and differentiating various activities and walking periods, the system also records the subject’s activity level over time, washroom use frequency, sleep/sedentary/active/out-of-home durations, current state, and gait parameters. Importantly, the system maintains privacy by not requiring the subject to wear or carry any additional devices

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

    Multifunction Radios and Interference Suppression for Enhanced Reliability and Security of Wireless Systems

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    Wireless connectivity, with its relative ease of over-the-air information sharing, is a key technological enabler that facilitates many of the essential applications, such as satellite navigation, cellular communication, and media broadcasting, that are nowadays taken for granted. However, that relative ease of over-the-air communications has significant drawbacks too. On one hand, the broadcast nature of wireless communications means that one receiver can receive the superposition of multiple transmitted signals. But on the other hand, it means that multiple receivers can receive the same transmitted signal. The former leads to congestion and concerns about reliability because of the limited nature of the electromagnetic spectrum and the vulnerability to interference. The latter means that wirelessly transmitted information is inherently insecure. This thesis aims to provide insights and means for improving physical layer reliability and security of wireless communications by, in a sense, combining the two aspects above through simultaneous and same frequency transmit and receive operation. This is so as to ultimately increase the safety of environments where wireless devices function or where malicious wirelessly operated devices (e.g., remote-controlled drones) potentially raise safety concerns. Specifically, two closely related research directions are pursued. Firstly, taking advantage of in-band full-duplex (IBFD) radio technology to benefit the reliability and security of wireless communications in the form of multifunction IBFD radios. Secondly, extending the self-interference cancellation (SIC) capabilities of IBFD radios to multiradio platforms to take advantage of these same concepts on a wider scale. Within the first research direction, a theoretical analysis framework is developed and then used to comprehensively study the benefits and drawbacks of simultaneously combining signals detection and jamming on the same frequency within a single platform. Also, a practical prototype capable of such operation is implemented and its performance analyzed based on actual measurements. The theoretical and experimental analysis altogether give a concrete understanding of the quantitative benefits of simultaneous same-frequency operations over carrying out the operations in an alternating manner. Simultaneously detecting and jamming signals specifically is shown to somewhat increase the effective range of a smart jammer compared to intermittent detection and jamming, increasing its reliability. Within the second research direction, two interference mitigation methods are proposed that extend the SIC capabilities from single platform IBFD radios to those not physically connected. Such separation brings additional challenges in modeling the interference compared to the SIC problem, which the proposed methods address. These methods then allow multiple radios to intentionally generate and use interference for controlling access to the electromagnetic spectrum. Practical measurement results demonstrate that this effectively allows the use of cooperative jamming to prevent unauthorized nodes from processing any signals of interest, while authorized nodes can use interference mitigation to still access the same signals. This in turn provides security at the physical layer of wireless communications

    Reference-free amplitude-based WiFi passive sensing

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    The parasitic exploitation of WiFi signals for passive sensing purposes is a topic that is attracting considerable interest in the scientific community. In an attempt at meeting the requirements for sensor compactness, easy deployment, and low cost, we resort to a non-coherent signal processing scheme that does not rely on the availability of a reference signal and relaxes the constraints on the sensor hardware implementation. Specifically, with the proposed strategy, the presence of a moving target echo is determined by detecting the amplitude modulation that it produces on the direct signal transmitted from the WiFi access point. We investigate the target discrimination capability of the resulting sensor against the competing interference background and we theoretically characterize the impact of undesired amplitude fluctuations in the received signal that are determined by causes other than the superposition of the target echo, thereby including the waveform properties. Hence, we propose different solutions to address the limitations identified, characterized by different complexities, and we investigate their advantages and drawbacks. The conceived signal processing schemes are thoroughly validated on both simulated and experimental data, collected in different operational scenarios

    Toward UWB Impulse Radio Sensing: Fundamentals, Potentials, and Challenges

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    Radio sensing is a rapidly emerging research field. It focuses on designing an integrated communication system that can also perform localization and radar functionalities sharing the same transmit signals and potentially the same hardware. Ultra-wideband (UWB) impulse radio is a promising technology for radio sensing because it offers a high-range resolution and direct access to the channel impulse response (CIR) to observe the multipath components (MPCs) of the wideband channel caused by scattering at target objects. This approach enables a wide range of functionalities and applications, especially in the field of mobility and transportation. The foundation is given by the signal propagation and channel modeling of the UWB channel, which is briefly revisited in this chapter. Based on the CIR and estimated MPCs the target object can be localized like a multistatic passive radar. The influence of geometry in a passive target localization system is studied by calculating the geometric dilution of precision (GDOP). In addition to passive localization more tasks and functionalities of radio sensing, are briefly introduced including detection, tracking, imaging, counting, and classification. The chapter concludes with further research directions and challenges in UWB radio sensing, especially for real-world use in the context of mobility applications
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