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Distinguishing among small UAVs with similar airframes and flight profiles is difficult using conventional micro-Doppler alone. We propose a cooperative, radar-centric identification scheme that equips propeller blades with passive nonlinear (harmonic) tags and encodes identity through tag radius and tag multiplicity (one or more tags per rotor; examples use one or two). In a continuous-wave harmonic receive chain tuned to the second harmonic, the radar isolates the tag’s nonlinear reradiation from linear clutter. In this framework, tag radius sets the maximum harmonic Doppler, and tag multiplicity determines the slow-time periodicity, yielding distinct, readable signatures. We validate the approach with simulation and a bench measurement of angular response for a printed tag, observe stable recovery of the expected harmonic Doppler peaks, and demonstrate clear separability between single- and two-tag cases. Because identity is conveyed by where tags are placed and by how many are used, rather than by airframe or maneuver, the method enables an RFID-like code space using battery-less components and standard harmonic-radar front ends.

Accurate analysis of a golfer's swing is critical for performance and injury prevention, but existing tools are often invasive, costly, or suffer from practical limitations. This paper demonstrates the viability of using a noninvasive, 60 GHz frequency-modulated continuous-wave (FMCW) radar for classifying golf swings. We conducted a systematic evaluation of sensor placement, comparing radar orientations at 0 degrees, 45 degrees, and 90 degrees relative to the swing plane. By analyzing the time-Doppler spectrograms and range profiles, we determined that a 45 degrees angle provides the optimal signal strength and captures the richest motion data. Using this configuration, we identified distinct spectrogram signatures for correct swings and common fundamental faults, including poor hip/shoulder rotation, extreme swing paths, and early extension. These findings establish a methodological foundation for developing cost-effective, real-time feedback systems that can help golfers improve their technique without intrusive sensors.

Doppler radar has been a topic of interest within the field of vital signs detection for a long time due to its contactless nature, giving it the ability to detect vital signs without impeding the user. Research on continuous wave radar (CW) for respiration detection has been conducted in the past, but this research primarily focuses on analyzing sleeping respiration or categorizing breathing into categories such as slow, normal, and fast. Analysis of controlled breathing techniques such as $4-7-8$ breathing, where the subject breathes in for four seconds, holds for seven seconds, and exhales for eight seconds, has been an unexplored area that can have applications within the meditative and controlled breathing space.

In this paper, a compact antenna pair with a measured isolation of about -51 dB between the antenna pairs after fabrication is reported. Two ground plane slots of quarter wavelength at the design frequency, sharing a common ground plane, are used as a transmit-receive antenna pair. An isolation unit with both ground plane and microstrip plane structures is used to improve the isolation. The structure is compact and doesn’t require any lumped components or complex geometry to realize the isolation unit. The antenna pair radiates in the broadside direction (along the y-axis), and the top plane with the microstrip line can subsequently be used to integrate the radar circuit, facilitating a compact and fully functional transceiver design.

This paper presents a ${\mathit{K}}$-band multiple-input multiple-output (MIMO) Doppler-division multiple-access (DDMA) stepped-frequency continuous-wave (SFCW) radar on an economical and rapid-prototyping printed circuit board (PCB) platform. The platform incorporates custom ${\mathit{K}}$-band digital phase shifters to achieve quadrature phase shift keying (QPSK)-based DDMA slow-time phase encoding with an integrated driving circuit compatible with standard digital control interfaces such as a microcontroller (MCU). This architecture supports simultaneous operation of all transmitting channels and digital beamforming (DBF) with modest hardware complexity. An array calibration framework adapted for DDMA mitigates MIMO channel variation, improving reliability in cluttered and dynamic environments. DDMA is a promising technique to achieve MIMO waveform orthogonality with simultaneous transmission from all transmitting elements, providing improved effective signal-to-noise ratio (SNR) compared to time-division multiplexed systems under matched operating conditions. Prior DDMA work primarily focuses on waveform or algorithmic enhancements and automotive applications, but applications of DDMA radar for human sensing and human awareness have received limited attention. To address this, this work presents the design, integration, and experimental characterization of a 4×4 MIMO DDMA SFCW prototype demonstrating potential for human-aware localization, validated with a wide range of 2-D localization experiments. Experimental validation includes controlled corner reflector measurements, mixed pedestrian-vehicle scenarios, and indoor multi-human scenarios in a realistic room environment. The system demonstrates 30-cm range resolution and 7.2$^\circ$ azimuth angular resolution.

ABSTRACT By analysing the response of low‐power radio waves reflected from human subjects, biomedical radar sensors enable remote monitoring without wearable devices and support emerging healthcare and human–machine interface applications. This paper reviews applications at the human–microwave frontier, including physiological sensing, non‐contact human–computer interfaces, driving behaviour recognition, human tracking, and early‐stage clinical studies. Despite rapid progress in radar‐based biomedical sensing, its integration into everyday life remains limited by body orientation, random motion, environmental clutter, and spectrum‐sharing constraints, all of which affect reliable signal acquisition. To address these challenges from a review perspective, this paper uses the bio‐inspired compound‐eye radio frequency (RF) vision concept as an organising framework for discussing spatial diversity, wavelength diversity, multi‐view beamforming, and data fusion as pathways towards more robust biomedical radar sensing. Recent advances in semiconductor technology have enabled compact radio‐frequency and millimetre‐wave integrated circuits with antenna‐in‐package solutions, making distributed and multi‐aperture radar sensing increasingly practical. Within this framework, compound‐eye RF vision can provide high‐fidelity depth and angular information, allowing radar systems to target specific body regions and extract physiological signals more reliably. Finally, this paper discusses indoor passive sensing based on ambient wireless signals and highlights the roles of advanced beamforming, multistatic detection, and spectrum‐efficient sensing in future human‐centred radar systems.

This paper presents the design, simulation, and experimental validation of an 8–16 GHz harmonic radar system integrated with two passive inkjet-printed nonlinear tags for wireless respiration monitoring. Unlike the previously reported 4–8 GHz implementation, the higher operating band provides greater spectral separation between transmit and receive frequencies, improving harmonic isolation, clutter rejection, and tag miniaturization. The radar employs an 8 GHz transmit path and a 16 GHz receive chain with high-linearity amplification and multi-stage filtering to suppress fundamental leakage. Each nonlinear tag utilizes a snowflake-based printed geometry integrating a Schottky diode for second-harmonic generation, with electromagnetic behavior optimized through full-wave simulation in High-Frequency Structure Simulator (HFSS). Two variants, Tag A and Tag B, were inkjet-printed using silver-coated copper ink on photo-paper substrates and differ in size and geometry to investigate the effect of physical scaling on harmonic performance. The radar hardware was implemented on a multilayer PCB platform and evaluated in an electronically active laboratory containing powered instruments and motion sources. During testing, each tag was attached to the subject’s chest beneath two clothing layers while a respiration belt provided ground-truth reference data. Four datasets—normal and rapid breathing for each tag—were analyzed in the time, frequency, and short-time Fourier transform (STFT) domains. The measured harmonic responses exhibited strong correlation with the reference respiration signals, confirming that the proposed 8–16 GHz harmonic radar with inkjet-printed nonlinear tags enables clutter-resilient, noncontact, and fully passive respiration monitoring suitable for biomedical sensing applications.

Technological advancements have enabled the implementation of software-defined radars (SDRadar) as low-cost, reconfigurable radar systems using software processing. The adaptability and reusability of SDRadar have expanded their application in many healthcare applications. An SDRadar is usually designed with a basic architecture that includes a transmitter, receiver, and a digital signal processor. The transmitter sends out radio waves, which are reflected, or penetrated and scattered, from the targeted object. Those reflected or scattered signals are captured by the received and processed using a digital signal processor to extract useful information. This flexibility allows SDRadar to be easily reprogrammed for different tasks without changing the hardware. To support and motivate researchers and practitioners of various scientific and engineering expertise, a state-of-the-art review of SDRadar, focusing on the healthcare applications of continuous waves, frequency-modulated continuous waves, and stepped-frequency continuous-wave modes, is presented. The review focuses on heart rate and respiration monitoring, as well as medical radar imaging, over a broad frequency range from 0.2 GHz to 20 GHz. Future research trends and potential advancements are also discussed.

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Magnetic particle imaging (MPI) is a new tomographic imaging technique that can quantitatively correlate MPI signal intensity to the spatial distribution of magnetic nanoparticle (MNP) tracers. Due to its non-ionizing nature, low background signal from biological matrices, high contrast, and relatively good spatial and temporal resolution, MPI has been actively studied and applied to biomedical imaging and is expected to reach the clinical stage soon. To further improve the spatial resolution limit in MPI, researchers have been working towards optimizing the image reconstruction algorithms, magnetic field profiles, tracer designs, circuitry, etc. Recent studies reported that lower excitation field amplitudes can improve spatial resolution, though this comes at the expense of lower MPI signal and tracer sensitivity. Different excitation field profiles directly affect the collective dynamic magnetizations of tracers recorded by the receiver coil in MPI. However, there is a gap between understanding the relaxation dynamics of MNP tracers, the signal-to-noise ratio (SNR) of MPI signals, and the MPI spatial resolution. In this work, we used a stochastic Langevin equation with coupled Brownian and Néel relaxations to model the magnetic dynamics of different MNP tracers subjected to varying excitation fields. We analyzed the collective time-domain dynamic magnetizations (M-t curves), magnetic-field hysteresis loops (M-H curves), point spread functions (PSFs), higher harmonics, and SNR of the third harmonic to understand how the excitation field affects MPI performance. We employed Full Width at Half Maximum and SNR as evaluation metrics for imaging resolution and signal quality, respectively. Our study supports previous findings on the impact of excitation field amplitude on MPI performance while offering more profound insights into the interplay of nonequilibrium Néel and Brownian relaxation, tracer core size, and SNR.

Magnetic nanoparticles (MNPs) are widely recognized as effective signal amplifiers for surface plasmon resonance (SPR)-based biosensors. Herein, we report that SPR sensors can be a useful tool to characterize the physicochemical properties of surface-functionalized iron oxide MNPs. In this work, a Kretschmann configuration-based SPR sensing platform with a scanning angular range of up to 17° is employed to identify the resonance conditions of different MNP suspensions. We demonstrate the feasibility of SPR for differentiating different surface coatings on the iron oxide MNPs, such as amine, biotin, and streptavidin, as well as distinguishing different magnetic core sizes (from 15 nm to 30 nm) and nanoparticle concentrations (from 0.013 mg/ml to 2.5 mg/ml). The SPR resonance angle shift, Δθ, is used as a crucial parameter for characterizing these physicochemical properties of MNPs floating within the surface of the metal layer that can directly interact with the surface plasmons, and the variation of their physicochemical properties is the reason causing a shift in the SPR resonance angle.

In recent years, radar technology has gained significant interest for its application in detecting vital signs. It has the potential to play a crucial role in identifying obstructive sleep apnea (OSA), a serious condition that disrupts breathing during sleep that can lead to cognitive impairment and cardiovascular diseases. Studies show that Positional Therapy offers an effective and low-cost treatment for OSA. While Positional Therapy is a promising treatment for OSA, it often requires manual intervention, limiting its accessibility. There remains a gap for the automatic detection and treatment of OSA. This paper proposes a novel approach to address this gap by integrating a system that uses continuous wave (CW) Doppler radar for the detection of OSA and the application of Positional Therapy, thereby improving the accuracy of diagnosis and the effectiveness of treatment.

This paper introduces a portable harmonic radar system paired with an innovative tag designed for non-invasive physiological monitoring in multi-person scenarios. Operating at a fundamental frequency of 4 GHz with a second harmonic at 8 GHz, this system can detect a specific person's respiratory activity through clothing when the battery-less tag was attached to the skin. With a multi-element antenna and integrated Schottky diode, the tag in the form of a small sticker is lightweight, flexible, and adheres comfortably to the human chest, enabling seamless monitoring when placed beneath clothing. The system's effectiveness was demonstrated in experiments involving two human subjects: the primary subject wore the tag for respiratory monitoring, while a second subject walking in various directions around the monitored individual. This harmonic radar system features effective clutter and interference rejection, detecting only the tag's movement on the chest while rejecting interferences from other moving objects. By harnessing the tag's unique harmonic response and the radar system's high sensitivity and selectivity to second-order harmonic, this setup provides an efficient, unobtrusive solution for real-time patient care. This work highlights the potential of advanced harmonic radar technology in health monitoring, establishing a foundation for future applications in both clinical and home environments.

This paper presents a novel K-Band Quadrature Phase Shift Keying (QPSK) phase-modulated continuous-wave (PMCW) radar front end architecture with digital I/Q constellation phase compensation and I/Q channel imbalance correction. Although QPSK is a very common form of digital phase modulation, it is rarely reported for PMCW radar systems, especially those designed on printed circuit board (PCB) technology. A MATLAB simulation platform is also developed and presented to help verify the benefits of QPSK PMCW radar for range detection.

Magnetic particle imaging (MPI) is a tracer-based tomographic imaging technique utilized in applications such as lung perfusion imaging, cancer diagnosis, stem cell tracking, etc. The goal of translating MPI to clinical use has prompted studies on further improving the spatial-temporal resolutions of MPI through various methods, including image reconstruction algorithm, scanning trajectory design, magnetic field profile design, and tracer design. Iron oxide magnetic nanoparticles (MNPs) are favored for MPI and magnetic resonance imaging (MRI) over other materials due to their high biocompatibility, low cost, and ease of preparation and surface modification. For core-shell MNPs, the tracers' magnetic core size and non-magnetic coating layer characteristics can significantly affect MPI signals through dynamic magnetization relaxations. Most works to date have assumed an ensemble of MNP tracers with identical sizes, ignoring that artificially synthesized MNPs typically follow a log-normal size distribution, which can deviate theoretical results from experimental data. In this work, we first characterize the size distributions of four commercially available iron oxide MNP products and then model the collective magnetic responses of these MNPs for MPI applications. For an ensemble of MNP tracers with size standard deviations of sigma, we applied a stochastic Langevin model to study the effect of size distribution on MPI imaging performance. Under an alternating magnetic field (AMF), i.e., the excitation field in MPI, we collected the time domain dynamic magnetizations (M-t curves), magnetization-field hysteresis loops (M-H curves), point-spread functions (PSFs), and higher harmonics from these MNP tracers. The intrinsic MPI spatial resolution, which is related to the full width at half maximum (FWHM) of the PSF profile, along with the higher harmonics, serve as metrics to provide insights into how the size distribution of MNP tracers affects MPI performance.

A major challenge of learning trombone as a beginner is accurately learning the locations of the slide positions. This study demonstrates the potential of using a frequency-modulated continuous wave (FMCW) radar system to identify and provide accurate feedback on slide position. The theory of FMCW radar is first presented, along with a tailor-made clutter suppression algorithm to reject stationary clutters in the context of slide detection. Experimental data using a commercial 60-GHz FMCW radar module was taken with a variety of trombone slide motions to verify its ability to detect slide position in lab-based and realistic musical practice environments. Radar and audio data were acquired in tandem to show correspondence with the slide positioning. The results from the experiments show good agreement with audio data and the ability to reject clutters, highlighting the potential for FMCW radar to be used as an educational tool to provide feedback while learning the trombone.

In this article, a novel method was proposed to extract heartbeat information based on a 2nd order differential technique complemented by leveraging the elevated strong harmonics of heartbeat in frequency domain signal by superimposing their magnitude to the fundamental frequency. A theoretical analysis of the working principle of the algorithm has been provided, along with a simulation, to demonstrate the algorithm's advantage in the existence of strong respiration harmonics. An experimental analysis was conducted, and the accuracy achieved using the proposed method was 1.47 Bpm for five subjects with a mean average error of over two minutes of collected data.

Microwave radar sensors have been used as wireless vital sign sensors for some time. After down-conversion to baseband, the radar output signals often require amplification before being digitized. AC-coupled amplifiers offer a simpler overall architecture compared to dc-coupled systems but suffer from long start times when used with frequencies in the range of human vital signs. Previous fast-start circuits have improved start time but introduce distortion at low frequencies. This paper proposes a new ac-coupled baseband amplifier architecture that uses switched MOSFETs to provide faster start time without impacting low frequency performance. The system theory shows its ability to improve start time, while experimental results using a benchtop and radar system demonstrate that the amplifier offers a simple and low-cost method of reducing start time without introducing distortion.

Magnetic hyperthermia therapy is an evolving treatment for tumors where magnetic nanoparticles (MNPs) are directed to the tumor and exposed to an alternating magnetic field (AMF). This induces localized heating, causing the apoptosis of cancer cells. Monitoring heat delivery in a noninvasive, real-time manner is crucial for predicting clinical outcomes. This precise control over the hyperthermia process allows for targeted temperature adjustments in the range of 42 degrees C-46 degrees C, effectively targeting cancer cells while minimizing damage to surrounding healthy tissue. Factors, such as MNP size, medium viscosity, and AMF frequency and amplitude, influence the hyperthermia performance. Optimizing these factors enhances heat dissipation through mechanisms, such as hysteresis loss and Neel and Brownian relaxations, improving the intrinsic loss power (ILP) of the MNPs. In this study, we meticulously measure the temperature-time curves (T-t curves) and ILP values of several commercially available iron oxide MNP products. By systematically varying the concentration and magnetic core size of the MNPs and tuning the frequency and amplitude of the AMF, we aim to elucidate how these factors collectively influence heat dissipation. This, in turn, enhances our understanding of the optimal conditions for in vivo hyperthermia treatment. Our results indicate that among the MNP products tested, the 30 nm single-core MNPs exhibited the highest ILP. Additionally, for different MNP concentrations, the 50 nm multi-core MNPs show the highest ILP at a concentration of 2 mg/mL.