Daniel Rodriguez

A new radar architecture that features a compact size and only one RF active device was designed, fabricated, and tested for small motion detection and human range tracking. Unlike conventional board level radar systems, it contains a single antenna and does not use any low noise amplifier (LNA) or circulator in the RF front-end. The I/Q amplitude and phase imbalance present on the system were measured to be <1% and 5.17°, respectively. Besides the local oscillator (LO), there is no other active device consuming dc power. The fabricated radar system has dimensions of 36 mm × 72 mm (L×W) and a power consumption of 290 mW in continuous operation. Moreover, a 24-GHz single channel radar system was designed, fabricated, and tested using the proposed architecture. The dimensions of fabricated board are 24 mm × 27 mm (L×W) and total power consumption of 800 mW dissipated by the local oscillator. The range tracking capabilities of the implemented radar systems were demonstrated by successfully tracking the range of a human target walking back and forth on a hallway. Moreover, the high sensitivity of the proposed quadrature 2-port monostatic Doppler radar was demonstrated by effectively measuring a sinusoidal movement with an amplitude of 2.5 μm with a 5.8-GHz carrier.

This article presents emulation and adverse attack scenarios for Doppler radar-based motion sensors and frequency-modulated continuous-wave (FMCW) radars employed for noninvasive vital signs measurement and human presence sensing. In contrast to existing radar threat models, the proposed model is tuned to mimic two characteristics of a human target measured by radars, i.e., the motion artifacts generated by a walking human and the inherent chest motion. Electronically synthesizing the abovementioned characteristics can interfere with the normal operation of radar systems used for automation, bioauthentication, and surveillance applications. The attacking/emulation systems were realized using commercially available radio frequency (RF) components. The 5.8-GHz benchtop prototypes of the Doppler-and FMCW-mode systems were designed, and experiments were conducted to validate the threat of these systems. First, a single-sideband (SSB) mixer is utilized to electronically modulate the continuous-wave (CW) signal transmitted by a Doppler radar to resemble a walking human subject. Next, fake human targets are injected into an FMCW radar by using an analog phase shifter that mimics the vital sign motion of a real human subject. In addition to impersonating the human vital sign motion, the FMCW mode spoofing system has the capability to alter the range of the human target without requiring any synchronization with the victim radar. The FMCW mode spoofing system successfully deceived two state-of-the-art human detection algorithms. Finally, a brief discussion is presented on the feasibility of using the proposed Doppler and FMCW mode spoofing device architecture as respective radar target emulators.

In the past decades, dramatic investments and growth in wireless communication have occupied more and more radio frequency (RF) spectrum and created a shortage in the available radio spectrum. Hence, spectrum efficiency is a critical issue at the forefront of the research. Compared with conventional radar sensors, which rely on a transmitter and a receiver to detect a target, microwave passive sensing does not require a dedicated transmitter. Therefore, microwave passive sensing can have lower power and lower cost while saving the RF spectrum that is becoming limited in the modern wireless era. Since RF signals exist ubiquitously, microwave passive sensing technology has tremendous opportunities. This article proposes a passive biomedical Doppler radar sensor that operates at the Wi-Fi 2.4-GHz band to detect physiological motions of human subjects with a third-party 2.4-GHz transmitter. The proposed passive radar does not require a reference signal. It has a simple architecture with an LNA and a customized single-input diode-based mixer to maximize the down-conversion gain. Experiment results demonstrated that the proposed passive radar receiver has a voltage gain of 53.9 dB from the antenna output to the mixer output, and it can measure the respiration rate and the heart rate of a human subject successfully. The measured respiration rate and heart rate match the results from a fingertip pulse monitor and a chest band respiration monitor, respectively. Gesture detection was also demonstrated with the proposed passive radar.

With the increasing demand for wireless sensors due to the growing Internet of Things (IoT) industry, it becomes desirable to use existing technologies to realize new sensing functions. As wireless power transfer (WPT) becomes a standard feature in smartphones, this paper studies the non-invasive classification of liquid solutions with different concentrations, based on the WPT technology already deployed in mobile devices. Average accuracies of up to 97.6% were achieved utilizing supervised machine learning for the classification of milk adulterated with different water volumes. For these experiments, milk concentrations of 100%, 80%, 60%, and 40% were used for classification. Additionally, singular value decomposition and boxplot analysis were used to reduce the radio frequency bandwidth needed for classification to 9.45 MHz, leading to a drastic reduction in hardware complexity and computational cost.

In this paper, a passive-intermodulation-based tracking system working with a frequency-modulated continuous-wave (FMCW) is proposed for target identification and localization. Signals in the microwave range are chosen to realize ranging purposes for the benefits of small device size, lightweight, and wide available bandwidth. Depending on whether the nonlinear properties of electrical components, such as diodes, transistors, and mixers, are exploited, the tracking systems can be categorized as linear and nonlinear systems. By nature, the linear tracking methods are vulnerable to surrounding clutter, such as furniture, walls, and other objects, since the reflection signals from clutter are of the same nature as the target. In comparison, the nonlinear detection methods are attractive owning to the fact that the majority of the clutter does not possess nonlinear properties. Hence, the nonlinear detection system does not “see” the linear clutter and only senses the target exhibiting nonlinear responses. Among all the nonlinear technologies, the intermodulation-based tracking and mapping approach has less path loss than the harmonic-based, smaller circuit size than the subharmonic-based, and simpler tag design and fewer signal licenses required than both of its counterparts. Therefore, in this work, the intermodulation-based technology is adopted, and a new nonlinear tracking system is designed to track the distance of the target in a complex indoor scenario crowded with unwanted objects.

Radar sensors have shown great potential for surveillance and security authentication applications. However, a thorough analysis of their vulnerability to spoofing or replay attacks has not been performed yet. In this paper, the feasibility of performing spoofing attacks to radar sensor is studied and experimentally verified. First, a simple binary phase-shift keying system was used to generate artificial spectral components in the radar's demodulated signal. Additionally, an analog phase shifter was driven by an arbitrary signal generator to mimic the human cardio-respiratory motion. Characteristic time and frequency domain cardio-respiratory human signatures were successfully generated, which opens possibilities to perform spoofing attacks to surveillance and security continuous authentication systems based on microwave radar sensors.

In this article, fully integrated binary phase shift keying (BPSK) tags are presented to work in conjunction with narrowband frequency-shift keying (FSK) radar for concurrent multitarget range tracking and vital signs sensing. Without the employment of any radio frequency (RF) mixer, the developed BPSK tag introduces a frequency offset by generating periodic phase shifts to the radar carrier frequencies with optimized power level. The theory of BPSK tag-based range tracking and vital signs sensing in conjunction with FSK radar signal is developed. An impedance-modulated 24-GHz tag architecture without any active RF components is proposed and its implementation and characterization are presented. The system performance is evaluated in the following residential indoor scenarios: single tag ranging, concurrent multiple tags and an untagged human target detection, and multiple tagged human targets tracking. Promising ranging performance demonstrates the potential for the proposed system to be adopted in various indoor tracking applications.

The massive deployment of wireless sensors is a fundamental piece in the growing internet of things (IoT) industry. Therefore, it is imperative to use already existing hardware to realize new sensing functions with very few or no hardware added. As wireless power transfer (WPT) and near field communication (NFC) become standard features in smart phones, this paper investigates beverage freshness sensing based on the WPT/NFC technology compatible with smart phones. A circuit model for the beverage-coil interaction was developed and the performance of features from different nature (e.g., magnitude, amplitude, phase) for classification was analyzed and tested. Accuracies up to 96.7% were achieved using supervised machine learning for milk freshness classification, when 5 different types of milk were used and up to 100% when just 2% fat milk was used for classification. Additionally, the radio frequency bandwidth needed for classification was reduced to 10 MHz using singular value decomposition (SVD) and boxplot analysis without affecting the classification accuracy for two different methods of feature extraction.

In all quadrature direct-conversion receivers, signal deterioration due to I/Q mismatch may happen, causing a mirrored signal to appear superimposed onto the desired signal, thereby destroying the orthogonality of the demodulated signal. This effect strongly affects radar systems over 100 GHz, since they are sensitive to small fabrication errors. In addition, when slow movements are measured with ac-coupled interferometric radars, coupling distortions are observed. In this article, these distortions were analyzed for interferometric radars and then resolved using a novel phase imbalance correction method for a 125-GHz radar. The effectiveness of the proposed solution was verified experimentally for speech information sensing and for small motion detection applications. By successfully measuring a 95-nm sinusoidal movement, the high sensitivity of millimeter-wave (mm-wave) radars was demonstrated. Moreover, noise analyses for small-motion interferometry radars have been presented and a model for sensitivity estimation was proposed.