A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications.

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Adjustment of rotation and saturation effects (AROSE) for CEST imaging.

PURPOSE: Endogenous CEST signal usually has low specificity due to contaminations from the magnetization transfer contrast (MTC) and other labile protons with overlapping or close Larmor frequencies. We propose to improve CEST signal specificity with adjustment of rotation and saturation effects (AROSE). METHODS: The AROSE approach measures the difference between CEST signals acquired with the same average irradiation power but largely different duty cycles, for example, a continuous wave or a high duty cycle pulse train versus a low duty cycle pulse train with a flip angle φ. Simulation, phantom, and in vivo rodent studies were performed to evaluate the characteristics of the AROSEφ signal. RESULTS: Simulation and experimental results show that AROSE2π is a low-pass filter that can suppress fast exchanging processes (e.g., >3000 s-1 ), whereas AROSEπ is a band-pass filter suppressing both fast and slow exchange (e.g., <30 s-1 ) rates. For other φ angles, the sensitivity and the exchange-rate filtering effect of AROSEφ falls between AROSEπ and AROSE2π . AROSE can also minimize MTC and improve the Larmor frequency selectivity of the CEST signal. The linewidth of the AROSE1.5π spectrum is about 60% to 65% when compared to the CEST spectrum measured by continuous wave. Depending on the needs of an application, the sensitivity, exchange-rate filtering, and Larmor frequency selectivity can be adjusted by varying the flip angle, duty cycle, and average irradiation power. CONCLUSION: Compared to conventional CEST signals, AROSE can minimize MTC and improve exchange rate filtering and Larmor frequency specificity.

Deciphering adiabatic rotating frame relaxometry in biological tissues.

PURPOSE: This work aims to unravel the intricacies of adiabatic rotating frame relaxometry in biological tissues. THEORY AND METHODS: The classical formalisms of dipolar relaxation R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ were systematically analyzed for water molecules reorienting on "fast" and "slow" timescales. These two timescales are, respectively, responsible for the absence and presence of R 1 ρ $$ {R}_{1\rho } $$ dispersion. A time-averaged R 1 ρ $$ {R}_{1\rho } $$ or R 2 ρ $$ {R}_{2\rho } $$ over an adiabatic pulse duration was recast into a sum of R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ , but with different weightings. These weightings depend on the specific modulations of adiabatic pulse waveforms. In this context, stretched hyperbolic secant ( HSn $$ HSn $$ ) pulses were characterized. Previously published H S 1 $$ HS1 $$ R 1 ρ $$ {R}_{1\rho } $$ , continuous-wave (CW) R 1 ρ $$ {R}_{1\rho } $$ , and R 1 $$ {R}_1 $$ measures from 12 agarose phantoms were used to validate the theoretical predictions. A similar validation was also performed on previously published HSn $$ HSn $$ R 1 ρ $$ {R}_{1\rho } $$ ( n $$ n $$ =1, 4, 8) and HS 1 $$ HS1 $$ R 2 ρ $$ {R}_{2\rho } $$ from bovine cartilage specimens. RESULTS: Longitudinal relaxation weighting decreases for HSn $$ HSn $$ pulses as n $$ n $$ increases. Predicted CW R 1 ρ cal $$ {R}_{1\rho}^{cal} $$ values from agarose phantoms align well with the measured CW R 1 ρ exp $$ {R}_{1\rho}^{exp} $$ values, as indicated by a linear regression function: R 1 ρ cal = 1.04 * R 1 ρ exp - 1.96 $$ {R}_{1\rho}^{cal}={1.04}^{\ast }{R}_{1\rho}^{exp}-1.96 $$ . The predicted adiabatic R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ from cartilage specimens are consistent with those previously measured, as quantified by: R 1 ρ , 2 ρ cal = 1.10 * R 1 ρ , 2 ρ exp - 0.41 $$ {R}_{1\rho, 2\rho}^{cal}={1.10}^{\ast }{R}_{1\rho, 2\rho}^{exp}-0.41 $$ . CONCLUSION: This work has theoretically and experimentally demonstrated that adiabatic R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ can be recast into a sum of R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ , with varying weightings. Therefore, any suggestions that adiabatic rotating frame relaxometry in biological tissues could provide more information than the standard R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ warrant closer scrutiny.

Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition.

PURPOSE: To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method. METHODS: Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient. RESULTS: The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well. CONCLUSION: The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.

Deep Neural Network-Based Phase-Modulated Continuous-Wave LiDAR.

LiDAR has high accuracy and resolution and is widely used in various fields. In particular, phase-modulated continuous-wave (PhMCW) LiDAR has merits such as low power, high precision, and no need for laser frequency modulation. However, with decreasing signal-to-noise ratio (SNR), the noise on the signal waveform becomes so severe that the current methods to extract the time-of-flight are no longer feasible. In this paper, a novel method that uses deep neural networks to measure the pulse width is proposed. The effects of distance resolution and SNR on the performance are explored. Recognition accuracy reaches 81.4% at a 0.1 m distance resolution and the SNR is as low as 2. We simulate a scene that contains a vehicle, a tree, a house, and a background located up to 6 m away. The reconstructed point cloud has good fidelity, the object contours are clear, and the features are restored. More precisely, the three distances are 4.73 cm, 6.00 cm, and 7.19 cm, respectively, showing that the performance of the proposed method is excellent. To the best of our knowledge, this is the first work that employs a neural network to directly process LiDAR signals and to extract their time-of-flight.

Vehicle Occupant Detection Based on MM-Wave Radar.

With the continuous development of automotive intelligence, vehicle occupant detection technology has received increasing attention. Despite various types of research in this field, a simple, reliable, and highly private detection method is lacking. This paper proposes a method for vehicle occupant detection using millimeter-wave radar. Specifically, the paper outlines the system design for vehicle occupant detection using millimeter-wave radar. By collecting the raw signals of FMCW radar and applying Range-FFT and DoA estimation algorithms, a range-azimuth heatmap was generated, visually depicting the current status of people inside the vehicle. Furthermore, utilizing the collected range-azimuth heatmap of passengers, this paper integrates the Faster R-CNN deep learning networks with radar signal processing to identify passenger information. Finally, to test the performance of the detection method proposed in this article, an experimental verification was conducted in a car and the results were compared with those of traditional machine learning algorithms. The findings indicated that the method employed in this experiment achieves higher accuracy, reaching approximately 99%.

A Review on Radar-Based Human Detection Techniques.

Radar systems are diverse and used in industries such as air traffic control, weather monitoring, and military and maritime applications. Within the scope of this study, we focus on using radar for human detection and recognition. This study evaluated the general state of micro-Doppler radar-based human recognition technology, the related literature, and state-of-the-art methods. This study aims to provide guidelines for new research in this area. This comprehensive study provides researchers with a thorough review of the existing literature. It gives a taxonomy of the literature and classifies the existing literature by the radar types used, the focus of the research, targeted use cases, and the security concerns raised by the authors. This paper serves as a repository for numerous studies that have been listed, critically evaluated, and systematically classified.

Evaluation of Lateral Radar Positioning for Vital Sign Monitoring: An Empirical Study.

Vital sign monitoring is dominated by precise but costly contact-based sensors. Contactless devices such as radars provide a promising alternative. In this article, the effects of lateral radar positions on breathing and heartbeat extraction are evaluated based on a sleep study. A lateral radar position is a radar placement from which multiple human body zones are mapped onto different radar range sections. These body zones can be used to extract breathing and heartbeat motions independently from one another via these different range sections. Radars were positioned above the bed as a conventional approach and on a bedside table as well as at the foot end of the bed as lateral positions. These positions were evaluated based on six nights of sleep collected from healthy volunteers with polysomnography (PSG) as a reference system. For breathing extraction, comparable results were observed for all three radar positions. For heartbeat extraction, a higher level of agreement between the radar foot end position and the PSG was found. An example of the distinction between thoracic and abdominal breathing using a lateral radar position is shown. Lateral radar positions could lead to a more detailed analysis of movements along the body, with the potential for diagnostic applications.

Remote Emotion Recognition Using Continuous-Wave Bio-Radar System.

The Bio-Radar is herein presented as a non-contact radar system able to capture vital signs remotely without requiring any physical contact with the subject. In this work, the ability to use the proposed system for emotion recognition is verified by comparing its performance on identifying fear, happiness and a neutral condition, with certified measuring equipment. For this purpose, machine learning algorithms were applied to the respiratory and cardiac signals captured simultaneously by the radar and the referenced contact-based system. Following a multiclass identification strategy, one could conclude that both systems present a comparable performance, where the radar might even outperform under specific conditions. Emotion recognition is possible using a radar system, with an accuracy equal to 99.7% and an F1-score of 99.9%. Thus, we demonstrated that it is perfectly possible to use the Bio-Radar system for this purpose, which is able to be operated remotely, avoiding the subject awareness of being monitored and thus providing more authentic reactions.

Single-Molecule Continuous-Wave Terahertz Rectification Spectroscopy and Microscopy.

We report rectification spectroscopy (RS) for single molecules performed with continuous-wave terahertz (CW THz) radiation at the tunneling junction of a scanning tunneling microscope (STM) at 8 K. CW THz-RS serves as a new technique in single-molecule vibrational and magnetic excitation spectroscopy besides inelastic electron tunneling spectroscopy (IETS). By quantitatively studying IETS and THz RS, we show that CW THz induces a sinusoidal bias modulation with amplitude linearly dependent on the THz far-field amplitude. Such THz-induced bias modulation amplitude appears to be sensitive to the THz beam alignment but insensitive to variation in the tunneling gap far smaller than the THz wavelength.

Guanidinium and amide CEST mapping of human brain by high spectral resolution CEST at 3 T.

PURPOSE: To extract guanidinium (Guan) and amide CEST on the human brain at 3 T MRI with the high spectral resolution (HSR) CEST combined with the polynomial Lorentzian line-shape fitting (PLOF). METHODS: Continuous wave (cw) turbo spin-echo (TSE) CEST was implemented to obtain the optimum saturation parameters. Both Guan and amide CEST peaks were extracted and quantified using the PLOF method. The NMR spectra on the egg white phantoms were acquired to reveal the fitting range and the contributions to the amide and GuanCEST. Two types of CEST approaches, including cw gradient- and spin-echo (cwGRASE) and steady state EPI (ssEPI), were implemented to acquire multi-slice HSR-CEST. RESULTS: GuanCEST can be extracted with the PLOF method at 3 T, and the optimum B 1 = 0.6 µ T $$ {\mathrm{B}}_1=0.6\kern0.2em \upmu \mathrm{T} $$ was determined for GuanCEST in white matter (WM) and 1.0 µT in gray matter (GM). The optimum B1  = 0.8-1 µT was found for amideCEST. AmideCEST is lower in both WM and GM collected with ssEPI compared to those by cwGRASE (ssEPI = [1.27-1.63]%; cwGRASE = [2.19-2.25]%). The coefficients of variation (COV) of the amide and Guan CEST in both WM and GM for ssEPI (COV: 28.6-33.4%) are significantly higher than those of cwGRASE (COV: 8.6-18.8%). Completely different WM/GM contrasts for Guan and amide CEST were observed between ssEPI and cwGRASE. The amideCEST was found to have originated from the unstructured amide protons as suggested by the NMR spectrum of the unfolded proteins in egg white. CONCLUSION: Guan and amide CEST mapping can be achieved by the HSR-CEST at 3 T combing with the PLOF method.

Cyanide replaces substrate in obligate-ordered addition of nitric oxide to the non-heme mononuclear iron AvMDO active site.

Thiol dioxygenases are a subset of non-heme mononuclear iron oxygenases that catalyze the O2-dependent oxidation of thiol-bearing substrates to yield sulfinic acid products. Cysteine dioxygenase (CDO) and 3-mercaptopropionic acid (3MPA) dioxygenase (MDO) are the most extensively characterized members of this enzyme family. As with many non-heme mononuclear iron oxidase/oxygenases, CDO and MDO exhibit an obligate-ordered addition of organic substrate before dioxygen. As this substrate-gated O2-reactivity extends to the oxygen-surrogate, nitric oxide (NO), EPR spectroscopy has long been used to interrogate the [substrate:NO:enzyme] ternary complex. In principle, these studies can be extrapolated to provide information about transient iron-oxo intermediates produced during catalytic turnover with dioxygen. In this work, we demonstrate that cyanide mimics the native thiol-substrate in ordered-addition experiments with MDO cloned from Azotobacter vinelandii (AvMDO). Following treatment of the catalytically active Fe(II)-AvMDO with excess cyanide, addition of NO yields a low-spin (S = 1/2) (CN/NO)-Fe-complex. Continuous wave and pulsed X-band EPR characterization of this complex produced in wild-type and H157N variant AvMDO reveal multiple nuclear hyperfine features diagnostic of interactions within the first- and outer-coordination sphere of the enzymatic Fe-site. Spectroscopically validated computational models indicate simultaneous coordination of two cyanide ligands replaces the bidentate (thiol and carboxylate) coordination of 3MPA allowing for NO-binding at the catalytically relevant O2-binding site. This promiscuous substrate-gated reactivity of AvMDO with NO provides an instructive counterpoint to the high substrate-specificity exhibited by mammalian CDO for L-cysteine.

Assessing maternal cardiac function by obstetricians: technique and reference ranges.

BACKGROUND: A strong body of evidence has now coalesced indicating that some obstetrical syndromes may result from maladaptive responses of the maternal cardiovascular system. Longitudinal studies have shown that these changes are complex and present before the clinical recognition of preeclampsia and fetal growth restriction, suggesting that hemodynamic maladaptation may play an etiologic role in obstetrical complications. Chronic hypertension is one of the most frequent complications of pregnancy, and recent evidence suggests that control of mild hypertension in early pregnancy improves outcome. The management of chronic hypertension can be improved by understanding specific cardiovascular hemodynamic abnormalities such as increased cardiac output or increased systemic vascular resistance, which can respond to either beta or calcium channel blockers, depending on the hemodynamic findings. Evaluation of maternal cardiac function has not been previously available to obstetrical healthcare providers using diagnostic ultrasound equipment used for fetal evaluation. OBJECTIVE: Obstetrical ultrasound machines may be configured for various probes (endovaginal, abdominal, 3D/4D, and cardiac). This study used a cardiac probe placed in the suprasternal notch to image and measure the descending aorta diameter and the velocity time integral using pulsed and continuous wave Doppler ultrasound in normal pregnant women between 11 and 39 weeks of gestation. These measurements were followed by computation of maternal left ventricular preload, afterload, contractility, and blood flow. STUDY DESIGN: This was a prospective cross-sectional study. A total of 400 pregnant women were recruited between 11 and 39 weeks of gestation. Imaging of the maternal aortic arch was performed by placing a cardiac probe in the suprasternal notch to identify the aortic arch using 2D and color Doppler ultrasound. The end-systolic diameter of the aorta was measured at the junction of the left subclavian artery with the descending aorta, which was followed by insonation of the descending aorta to obtain the Doppler waveform. Following insonation of the descending aorta, measurements of the aortic diameter, velocity time integral, ejection time, mean pressure gradient, heart rate, maternal weight and height, and systolic and diastolic blood pressures were entered into an Excel spreadsheet to compute the following: (1) preload measurements of stroke volume, stroke volume index, and stroke work index; (2) afterload measurements of systemic vascular resistance and the potential-to-kinetic energy ratio; (3) contractility measurements of inotropy and the Smith-Madigan inotropy index; and (4) blood flow measurements of cardiac output and the cardiac output index. Fractional polynomial regression analysis was performed for each of the above measurements using gestational age as the independent variable. RESULTS: The diastolic and mean arterial blood pressure decreased from 11 to 18 weeks of gestation and then increased until term. The afterload measurements demonstrated similar characteristics, as all values decreased from 11 weeks until the mid and late second trimester, after which all values increased until term. Changes in contractility demonstrated an increase from 11 weeks to 25 to 28 weeks, followed by a decline until term. Changes in blood flow demonstrated an increase from 11 to 27 weeks and then declined until term. The continuous wave Doppler values were greater than the pulsed Doppler values except for the contractility measurements. Examples of abnormal cardiac measurements were identified in pregnant patients with hypertension and fetal growth restriction. An Excel calculator was created to provide quick computation of z-score measurements and their corresponding centiles described in this study. CONCLUSION: The technique for evaluation of maternal cardiac function described in this study would allow screening of maternal left ventricular preload, afterload, contractility, and blood flow in the obstetrical clinical milieu once a cardiac probe is acquired for obstetrical ultrasound machines used for fetal evaluation. The above measurements would allow the clinician to select appropriate hypertensive medication on the basis of the results of the evaluation of the maternal left ventricle.

Implementation of continuous-wave Doppler ultrasound to detect the high-risk foetus in the low-risk mother: lessons from South Africa.

INTRODUCTION: Detecting the risk of stillbirth during pregnancy remains a challenge. Continuous-wave Doppler ultrasound (CWDU) can be used to screen for placental insufficiency, which is a major cause of stillbirths in low-risk pregnant women. This paper describes the adaptation and implementation of screening with CWDU and shares critical lessons for further rollout. Screening of 7088 low-risk pregnant women with Umbiflow™ (a CWDU device) was conducted in 19 antenatal care clinics at nine study sites in South Africa. Each site comprised a catchment area with a regional referral hospital and primary healthcare antenatal clinics. Women with suspected placental insufficiency as detected by CWDU were referred for follow-up at the hospital. A 35-43% reduction in stillbirths was recorded. METHODS: The authors followed an iterative reflection process using the field and meeting notes to arrive at an interpretation of the important lessons for future implementation of new devices in resource-constrained settings. RESULTS: Key features of the implementation of CWDU screening in pregnancy combined with high-risk follow-up are described according to a six-stage change framework: create awareness; commit to implement; prepare to implement; implement; integrate into routine practice; and sustain practice. Differences and similarities in implementation between the different study sites are explored. Important lessons include stakeholder involvement and communication and identifying what would be needed to integrate screening with CWDU into routine antenatal care. A flexible implementation model with four components is proposed for the further rollout of CWDU screening. CONCLUSIONS: This study demonstrated that the integration of CWDU screening into routine antenatal care, combined with standard treatment protocols at a higher-level referral hospital, can be achieved with the necessary resources and available maternal and neonatal facilities. Lessons from this study could contribute to future scale-up efforts and help to inform decisions on improving antenatal care and pregnancy outcomes in low- and middle-income countries.

The efficacy and safety of micropulse transscleral laser treatment in glaucoma: a systematic review and meta-analysis.

OBJECTIVE: Micropulse transscleral laser treatment (mTLT) is the latest alternative intraocular pressure (IOP) lowering approach for glaucoma patients. This meta-analysis aims to evaluate the efficacy and safety of mTLT and continuous wave transscleral cyclophotocoagulation (CW-TSCPC) for the treatment of glaucoma. METHODS: We searched the PubMed, Embase, and Cochrane Library of Systematic Reviews databases from January 2000 to July 2022 to identify studies that, evaluated the efficacy and safety of mTLT in glaucoma. There were no restrictions regarding study type, patient age, or type of glaucoma. We analysed the reduction in IOP and the number of anti-glaucoma medications (NOAM), retreatment rates, and complications between mTLT and CW-TSCPC treatment. Publication bias was conducted for evaluating bias. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA 2020) reporting guideline. RESULTS: We identified 6 eligible studies of which only 2 RCTs and 386 participants with various types of glaucoma at different stages were ultimately included. The results revealed significant IOP decreases after mTLT up to 12 months and significant NOAM reductions at 1 month (WMD=-0.30, 95% CI -0.54 to 0.06), and 3 months (WMD=-0.39, 95% CI -0.64 to 0.14) in mTLT compared to CW-TSCPC. Moreover, the retreatment rates (Log OR=-1.00, 95% CI -1.71 to -0.28), hypotony (Log OR=-1.21, 95% CI -2.26 to -0.16), prolonged inflammation or uveitis (Log OR=-1.63, 95% CI -2.85 to -0.41), and worsening of visual acuity (Log OR=-1.13, 95% CI -2.19 to 0.06) occurred less frequently after mTLT. CONCLUSION: Our results demonstrated that mTLT could lower the IOP until 12 months after treatment. mTLT seems to have a lower risk of retreatment after the first procedure, and mTLT is superior to CW-TSCPC with respect to safety. Studies with longer follow-up durations and larger sample sizes are necessary in the future. TRIAL REGISTRATION NUMBER: INPLASY202290120.

FMCW Radar System Interference Mitigation Based on Time-Domain Signal Reconstruction.

In this study, an interference detection and mitigation method is proposed for frequency-modulated continuous-wave radar systems based on time-domain signal reconstruction. The interference detection method uses the difference in one-dimensional fast Fourier transform (1D-FFT) results between targets and interferences. In the 1D-FFT results, the target appears as a peak at the same frequency point for all chirps within one frame, whereas the interference appears as the absence of target peaks within the first or last few chirps within one frame or as a shift in the target peak position in different chirps. Then, the interference mitigation method reconstructs the interference signal in the time domain by the estimated parameter from the 1D-FFT results, so the interference signal can be removed from the time domain without affecting the target signal. The simulation results show that the proposed interference mitigation algorithm can reduce the amplitude of interference by about 25 dB. The experimental results show that the amplitude of interference is reduced by 20-25 dB, proving the effectiveness of the simulation results.

Frequency Modulation Control of an FMCW LiDAR Using a Frequency-to-Voltage Converter.

An FMCW LiDAR (frequency-modulated continuous-wave light detection and ranging) is a sensor that can measure distance using optical interference frequency (fb). This sensor has recently attracted interest because it is robust to harsh environmental conditions and sunlight due to the wave properties of the laser. Theoretically, when the frequency of the reference beam is linearly modulated, a constant fb is obtained with respect to the distance. However, when the frequency of the reference beam fails to be linearly modulated, the distance measurement is not accurate. In this work, linear frequency modulation control using frequency detection is proposed to improve the distance accuracy. The FVC (frequency to voltage converting) method is used to measure fb for high-speed frequency modulation control. The experimental results show that linear frequency modulation control using an FVC improves FMCW LiDAR performance in terms of control speed and frequency accuracy.

Robust Hand Gesture Recognition Using a Deformable Dual-Stream Fusion Network Based on CNN-TCN for FMCW Radar.

Hand Gesture Recognition (HGR) using Frequency Modulated Continuous Wave (FMCW) radars is difficult because of the inherent variability and ambiguity caused by individual habits and environmental differences. This paper proposes a deformable dual-stream fusion network based on CNN-TCN (DDF-CT) to solve this problem. First, we extract range, Doppler, and angle information from radar signals with the Fast Fourier Transform to produce range-time (RT) and range-angle (RA) maps. Then, we reduce the noise of the feature map. Subsequently, the RAM sequence (RAMS) is generated by temporally organizing the RAMs, which captures a target's range and velocity characteristics at each time point while preserving the temporal feature information. To improve the accuracy and consistency of gesture recognition, DDF-CT incorporates deformable convolution and inter-frame attention mechanisms, which enhance the extraction of spatial features and the learning of temporal relationships. The experimental results show that our method achieves an accuracy of 98.61%, and even when tested in a novel environment, it still achieves an accuracy of 97.22%. Due to its robust performance, our method is significantly superior to other existing HGR approaches.

Reconstruction of Range-Doppler Map Corrupted by FMCW Radar Asynchronization.

Frequency-modulated continuous wave (FMCW) radar system synchronization using external clock signals can cause repeated Range-Doppler (R-D) map corruption when clock signal asynchronization problems occur between the transmitter and receiver. In this paper, we propose a signal processing method for the reconstruction of the corrupted R-D map owing to the FMCW radar's asynchronization. After calculating the image entropy for each R-D map, the corrupted ones are extracted and reconstructed using the normal R-D maps acquired before and after the individual maps. To verify the effectiveness of the proposed method, three target detection experiments were conducted: a human target detection in an indoor environment and a wide place and a moving bike-rider target detection in an outdoor environment. The corrupted R-D map sequence of observed targets in each case was reconstructed properly and showed the validity by comparing the map-by-map range and speed changes in the detected target with the ground-truth information of the target.

DNN-Based Estimation for Misalignment State of Automotive Radar Sensor.

The reliability and safety of advanced driver assistance systems and autonomous vehicles are highly dependent on the accuracy of automotive sensors such as radar, lidar, and camera. However, these sensors can be misaligned compared to the initial installation state due to external shocks, and it can cause deterioration of their performance. In the case of the radar sensor, when the mounting angle is distorted and the sensor tilt toward the ground or sky, the sensing performance deteriorates significantly. Therefore, to guarantee stable detection performance of the sensors and driver safety, a method for determining the misalignment of these sensors is required. In this paper, we propose a method for estimating the vertical tilt angle of the radar sensor using a deep neural network (DNN) classifier. Using the proposed method, the mounting state of the radar can be easily estimated without physically removing the bumper. First, to identify the characteristics of the received signal according to the radar misalignment states, radar data are obtained at various tilt angles and distances. Then, we extract range profiles from the received signals and design a DNN-based estimator using the profiles as input. The proposed angle estimator determines the tilt angle of the radar sensor regardless of the measured distance. The average estimation accuracy of the proposed DNN-based classifier is over 99.08%. Therefore, through the proposed method of indirectly determining the radar misalignment, maintenance of the vehicle radar sensor can be easily performed.