Range Profile Research Articles

Choice and impact of frequency increment in direct digital synthesiser (DDS)‐based linear FMCW radar

AbstractFMCW radar is a popular technique for radar sensors. A Direct Digital Synthesiser (DDS) is commonly used to generate the required linear frequency sweep. DDS devices are widely‐available and easy to configure in terms of the key radar parameters of sweep bandwidth and pulse duration. They generate a step‐approximation to a linear frequency sweep for which the frequency increment parameter also needs to be defined. However, there is little information available in the literature to guide radar designers on the choice of this parameter. As a result, most designs are based on an empirical estimate of the DDS frequency increment. The aim is to provide an analytic basis and design rules for the choice of this parameter. Two principal types of FMCW radar (direct sampling and deramp) are studied to determine the effect on the range profile of the finite DDS frequency increment. It is shown that a set of spurs appears around each target response. Analytic expressions are derived to quantify the amplitude and distribution of these spurs from which simple design rules are presented to allow an informed choice of DDS frequency increment. These analytic results are convincingly validated using numerical simulations and experimental measurements.

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.

HDT network: A high‐resolution range profile multi‐target detection and tracking method based on neural network

AbstractIn radar target detection and tracking tasks, the detection algorithm and data association algorithm are the primary technologies. The accuracy of detection, stability of tracking and processing speed are the key points to accomplishing effective high‐resolution range profile (HRRP) multi‐target tracking (MTT). Classic HRRP target tracking algorithms conduct the detection by extracting handcraft features and conduct tracking based on the data association algorithm. With the development of neural network methods, deep learning methods have been widely applied in target detection and tracking. An HRRP detection and tracking (HDT) network based on neural networks is proposed, which includes three steps: Firstly, the HRRP signal is processed by a convolutional neural network detector to extract the feature of the origin signal and generate the detection measurement. Secondly, a predicted measurement is generated by a Kalman filter, which estimates the current state of the target based on its previous states and the detection measurement. Finally, the ReID network calculates the cosine similarity between the tracks and measurements to associate them and a linear sum assignment operation is used to match the tracks and measurements. By using the proposed algorithm, the HDT network is capable of detecting and tracking multiple targets in complex cluttered environments with high accuracy. Experimental results on an HRRP dataset collected by a moving radar platform show the outstanding performance of the HDT network, including detection accuracy, track integrity and real‐time MTT.

Mapping non-axisymmetric velocity fields of external galaxies

ABSTRACT Disc galaxies are typically in a stable configuration where matter moves in almost closed circular orbits. However, non-circular motions caused by distortions, warps, lopsidedness, or satellite interactions are common and leave distinct signatures on galaxy velocity maps. We develop an algorithm that uses an ordinary least squares method for fitting a non-axisymmetric model to the observed two-dimensional line-of-sight velocity map of an external galaxy, which allows for anisotropic non-circular motions. The method approximates a galaxy as a flat disc, which is an appropriate assumption for spiral galaxies within the optical radius where warps are rare. In the outer parts of H i distributions, which may extend well into the warp region, we use this method in combination with a standard rotating tilted ring model to constrain the range of radii where the flat disc assumption can be conservatively considered valid. Within this range, the transversal and radial velocity profiles, averaged in rings, can be directly reconstructed from the velocity map. The novelty of the algorithm consists in using arc segments in addition to rings; in this way, spatial velocity anisotropies can be measured in both components, allowing for the reconstruction of angularly resolved coarse-grained two-dimensional velocity maps. We applied this algorithm to 25 disc galaxies from the THINGS sample, for which we can provide 2D maps of both velocity components.

A new method for vital sign detection using FMCW radar based on random body motion cancellation.

In this study, we present a new method for acquiring human vital signs using a Range-Doppler matrix (RDM) of FMCW radar data and a Gaussian interpolation algorithm (GIA). First, the RDM is derived by applying a two-dimensional fast Fourier transform (2D-FFT) to the radar data, and the GIA is applied in the Doppler dimension to estimate the target velocity signal. Subsequently, a robust enhanced trend filtering (RETF) algorithm is used to eliminate the large-scale body motion from the vital signs. Finally, the time-varying filter-based empirical mode decomposition (TVF-EMD) algorithm is employed to extract the respiratory and heartbeat intrinsic mode functions (IMFs), which are filtered according to their respective spectral power to obtain the respiratory and heartbeat frequencies. The proposed method was evaluated using vital signs data collected from seven volunteers (4 males and 3 females) with Texas Instrument's AWR1642, and the results were compared with data from a reference monitor. The experiments showed that the method had an accuracy of 93 % for respiration and 95 % for heart rate in the presence of random body movements. Unlike traditional radar-based vital signs detection methods, this approach does not rely on range bin selection of the range profile matrix (RPM), thereby avoiding phase wrap problems and producing more accurate results. Currently, research in this field is limited.

Sliding Scattering Center Extraction for Streamlined Radar Targets

Modern man-made targets with high-speed movement capabilities are often designed as special streamlined structures. As a result, when illuminated by radar, the surface of such targets will produce a sliding scattering center whose position changes with the radar line of sight. In this paper, we present a feature extraction technique for this kind of scattering centers. The trajectory of the equivalent scattering points in the one-dimensional (1-D) high-resolution range profile (HRRP) sinogram is first predicted by utilizing the special geometric characteristics of sliding scatterers. The parameters of sliding scattering features are then extracted by combining the basis pursuit algorithm with the predicted trajectory. Examples from both numerical and measured data are presented to demonstrate the usefulness of the proposed technique.

Motion Parameters Estimation and HRRP Reconstruction of Maneuvering Weak Target for Wideband Radar Based on SKT-ELVD

Compared with narrowband radars, the high-resolution range profile (HRRP) acquired by wideband radars contain abundant target information that is useful for detection and recognition. However, more and more threatening targets are of low observability and high maneuverability. Therefore, reconstructing HRRPs of maneuvering weak targets from low signal-to-noise ratio (SNR) echoes is a significant but challenging problem. To estimate motion parameters and reconstruct high-SNR HRRP, this paper proposes a long-time coherent integration (LTCI) algorithm based on subband keystone transform (SKT) and extended Lv's distribution (ELVD). In this paper, the range-spread target (RST) assumption is applied in the LTCI processing. Moreover, the proposed SKT-ELVD operations have excellent performance on range migration (RM) correction and integration gain. The proposed algorithm can be of effectiveness in lower SNR conditions, since more energy of target's echo can be accumulated. Theoretical results are initially supported by sufficient simulation examples. Finally, the validity of the proposed algorithm is confirmed by experimental data.

Target Measurement in Radio Frequency Simulation Using Code-Interrupted Transmitting and Receiving of Pulse Signals

The interrupted transmitting and receiving (ITR) has been utilized in radio frequency simulation to conduct target measurement with pulse signal. Because the ITR results in partly missing of pulse signal, the spectrum aliasing occurs and the target range profile is difficult to be obtained. Therefore, frequency domain filtering and sparse reconstruction are proposed to recover the target range profile. However, frequency domain filtering is ineffective when wideband signal is utilized. The calculation of sparse reconstruction is complex and the reconstruction performance may be poor for some cases of ITR parameters. To solve this problem, the code-interrupted transmitting and receiving (code-ITR) of pulse signal is proposed in this paper. Firstly, the ITR sequences is coded according the duty ratio of each sub-pulse. Secondly, the echo combination and cancellation are processed to eliminate the false peaks in the range profile of ITR echo. By using the code-ITR and echo processing method, the range profile can be obtained for target measurement. Simulations and experiments are performed to verify the effectiveness of the proposed method.

Sea Surface Moving Target Detection Using a Modified Keystone Transform on Wideband Radar Data

The echoes collected by wideband radar systems provide abundant information on target scatterers, which is beneficial to target detection, classification, and recognition. However, as the radar range resolution increases, range cell migration (RCM) during the coherent integration (CI) period happens much easier, which may cause a degradation of target detection probability. In addition, due to the target’s orientation and structure relative to the radar, the distribution characteristics of the target scatterers in high-resolution range profiles (HRRPs) and the detection window length may vary from pulse to pulse, which may reduce the performance of traditional energy integration (EI) detectors. To solve those problems, moving range-spread target (RST) detection combining the modified keystone transform (MKT) and improved EI (IEI) is proposed in this paper. Firstly, based on waveform entropy minimization, MKT using hunter–prey optimization (HPO) is introduced to reduce the CI gain loss. The target Doppler ambiguity factor is estimated using such an effective optimization technique. Then, the IEI detector optimized by the adaptive threshold and detection window is utilized to achieve target detection, which minimizes the sensitivity of the traditional EI detector to the detection window length. The proposed method significantly improves the performance of moving RSTs in sea clutter without prior knowledge of the target Doppler ambiguity factor. Experiments are conducted by comparing the proposed method with other competing methods on both simulation data and real sea clutter data. The results demonstrate that the proposed method can obtain the CI more efficiently and has a higher detection probability.

Multi-Source HRRP Target Fusion Recognition Based on Time-Step Correlation

Aiming at the limitations of a single High Resolution Range Profile (HRRP) in recognition, this paper proposes a Time step Correlation-based Feature Fusion (TCFF) method. This method calculates the covariance matrix at the time step of the two features extracted by the two channels, and assigns different weights to the time step according to the strength of the covariance correlation for feature fusion. The experimental results on the simulated ship target HRRP dataset show that the feature fusion method can achieve better recognition performance than the single channel model. Compared with simple feature fusion such as element addition and element contacting, it can also achieve better recognition results.

Near-Field IPO for Analysis of EM Scattering from Multiple Hybrid Dielectric and Conductor Target and High Resolution Range Profiles

Aiming at improving the accuracy and efficiency of scattering information from multiple targets in near-field regions, this paper proposes a near-field iterative physical optics (IPO) method based on a modified near-field Green’s function for the composite electromagnetic scattering analysis of multiple hybrid dielectric and conductor targets. According to the electric field and magnetic field integral equation, the electric and magnetic current were updated utilizing the Jacobi iteration method. Then, by introducing an expansion center lying in the neighborhood of the source point, Green’s function was modified for near-field scattering between multiple hybrid dielectric and conductor targets. To accelerate the implementation of the procedure, the multilevel fast multipole method, the fast far-field approximation, and parallel multicore programming were introduced. Numerical results indicate that there is good agreement between the results calculated by the near-field IPO method and MLFMM solver in commercial software FEKO while significantly reducing the computational burden. To fully exploit the scattering information, the high resolution range profiles (HRRP) of different targets under different conditions were analyzed, which can be further applied for automatic target detection and recognition.

Range profile analysis of buried objects in layered media based on efficient full-wave simulation

The high-resolution range profiles (RPs) of 3-D objects buried in layered media are investigated. In order to simulate the RPs efficiently, wideband scattered fields are calculated by a method of moments (MoM) based fast algorithm, i.e. characteristic basis function method (CBFM). To achieve fast frequency sweep, an adaptive frequency sampling strategy (AFS) is implemented to accelerate the broadband simulation. Then by using the inverse discrete Fourier transform (IDFT), RPs of the object are obtained. To validate the proposed approach, range locations are predicted qualitatively based on the ray theory. Moreover, the ray approach also enables the physical interpretation of the scattering mechanisms corresponding to the peaks, for example, the specular reflection, the edge diffraction, and the higher-order effects. Since different scattering centers (SCs) dominate in different directions, the RPs are aspect dependent. Furthermore, the RPs are also dependent on the lossy and dispersive effects of the layered medium. Numerical results demonstrate that the peaks are significantly reduced when the layered medium is lossy, especially those due to the higher-order interactions between the object and the interfaces.

Funkční hodnocení laryngoskopického vyšetření a souvislost s kvalitou hlasu a parametry hlasového pole

Summary Introduction: Previous laryngoscopy evaluation protocols have mostly focused on assessment of glottal status and morphological description of vocal folds’ shape and oscillations. The basic functional manifestations of laryngeal use, according to new protocols, include a description of supraglottic laryngeal activity. Methods: Laryngoscopic evaluation was performed as a perceptual test, performed online, using a web-based application. The degree and type of glottal insufficiency and the degree of anterior, posterior compression and lateral-medial (L-M) compression separately for each side were evaluated by a total of 15 respondents in a total of 26 video recordings of laryngoscopic examinations. In addition, the correlations between listening evaluations of the voice using modified GRBAS scales and voice range profile parameters were investigated. Results: The ratings of the laryngoscopic scales had well to excellent agreement. Agreement for type of insufficiency was just moderate. The associated ratings of L-M compression on the right and left sides showed correlations. For listening evaluation, medial compression was found to be related to the perception of habitual voice strain, and to strain and instability in the pitch range of the change of registers of the singing voice. Degree of insufficiency predicted less fullness of habitual voice in general but was also related to vocal dyspnea and weakness when calling. At the same time, it was largely responsible for the deterioration of the quality of the singing voice. Medial compression systematically reduced pitch range and the area of the voice range profile. Conclusion: The results of the perceptual evaluation can be used in further education. On their basis, didactic material for training the assessment of supraglottic laryngeal activity was prepared and published in the form of an online tutorial. The degree of insufficiency generally affects various characteristics of the speaking and singing voice. Medial compression systematically affects only the strain of the speaking voice, while in the singing voice it accentuates the strain and instability of the transitional region between registers and impairs the production of high pitches. Key words laryngoscopy – visual evaluation – voice range profile – GRBAS

A Radar Detection Method of Reentry Target Based on Frequency-Domain Processing

When the reentry target passes through the earth’s atmosphere, its surface is covered with a layer of plasma sheath. In the process of radar detection of the reentry target, the echo signal will couple with multi-Doppler frequency components and form multiple mismatch effects with matched filter, which will produce false targets on the 1-D range profile. Meanwhile, the excessive speed of the reentry target will lead to the phenomenon of migration through range cells (MTRCs), which will further affect the detection and recognition of the target. This article proposes an improved frequency-domain compensation method that aims at false target and cross-range unit migration. By constructing the intrapulse Doppler frequency and interpulse Doppler frequency compensation functions, the multiperiod echo signal is processed to eliminate the MTRC phenomenon and improve the energy gain of the real target. Finally, the feasibility of the proposed algorithm is verified by simulation, which lays a theoretical foundation for the effective detection and reliable tracking of plasma-sheath-covered targets.

An Accurate Echo-Acquisition Method for PEC/Coated Targets by GTD-Based Gridless Compressed Sensing

A novel geometrical theory of diffraction (GTD)-based echo-generation approach for perfectly electromagnetic conducting (PEC) and coated targets is proposed, which applies gridless compressed sensing (CS). First, the GTD model for both the PEC and coated targets is established. These GTD models can thus be used to obtain the scattering-echo. The gridless CS method is then used to estimate the GTD model’s phase information, offering a continuous parametric estimation. Next, the genetic algorithm (GA) is used to determine the amplitude and frequency dependency. Finally, the scattering echo at various observed angles can be quickly recorded, yielding high-resolution range profile imaging results. The numerical results show that the proposed method predicts echo more accurately than traditional optimization methods.

Pharmacokinetics and pharmacogenomics of clozapine in an ancestrally diverse sample: a longitudinal analysis and genome-wide association study using UK clinical monitoring data

The antipsychotic, clozapine, is the only licensed drug against the treatment-resistant symptoms that affect 20-30% of people with schizophrenia. Clozapine is markedly underprescribed, partly because of concerns about its narrow therapeutic range and adverse drug reaction profile. Both concerns are linked to drug metabolism, which varies across populations globally and is partly genetically determined. Our study aimed to use a cross-ancestry genome-wide association study (GWAS) design to investigate variations in clozapine metabolism within and between genetically inferred ancestral backgrounds, to discover genomic associations to clozapine plasma concentrations, and to assess the effects of pharmacogenomic predictors across different ancestries. In this GWAS, we analysed data from the UK Zaponex Treatment Access System clozapine monitoring service as part of the CLOZUK study. We included all available individuals with clozapine pharmacokinetic assays requested by their clinicians. We excluded people younger than 18 years, or whose records contained clerical errors, or with blood drawn 6-24 h after dose, a clozapine or norclozapine concentration less than 50 ng/mL, a clozapine concentration of more than 2000 ng/mL, a clozapine-to-norclozapine ratio outside of the 0·5-3·0 interval, or a clozapine dose of more than 900 mg/day. Using genomic information, we identified five biogeographical ancestries: European, sub-Saharan African, north African, southwest Asian, and east Asian. We did pharmacokinetic modelling, a GWAS, and a polygenic risk score association analysis using longitudinal regression analysis with three primary outcome variables: two metabolite plasma concentrations (clozapine and norclozapine) and the clozapine-to-norclozapine ratio. 19 096 pharmacokinetic assays were available for 4760 individuals in the CLOZUK study. After data quality control, 4495 individuals (3268 [72·7%] male and 1227 [27·3%] female; mean age 42·19 years [range 18-85]) linked to 16 068 assays were included in this study. We found a faster average clozapine metabolism in people of sub-Saharan African ancestry than in those of European ancestry. By contrast, individuals with east Asian or southwest Asian ancestry were more likely to be slow clozapine metabolisers than those with European ancestry. Eight pharmacogenomic loci were identified in the GWAS, seven with significant effects in non-European groups. Polygenic scores generated from these loci were associated with clozapine outcome variables in the whole sample and within individual ancestries; the maximum variance explained was 7·26% for the metabolic ratio. Longitudinal cross-ancestry GWAS can discover pharmacogenomic markers of clozapine metabolism that, individually or as polygenic scores, have consistent effects across ancestries. Our findings suggest that ancestral differences in clozapine metabolism could be considered for optimising clozapine prescription protocols for diverse populations. UK Academy of Medical Sciences, UK Medical Research Council, and European Commission.

Jamming of ISAR Imaging With Time-Modulated Metasurface Partially Covered on Targets

The phase information of the echo is essential for inverse synthetic aperture radar (ISAR) imaging. Time-modulated metasurface (TMM) generates time-varying reflection phase that can modulate the phase of echo, thus enabling jamming of ISAR imaging, which has great potential for real applications. In practice, covering the whole target with TMM is difficult to achieve. Consequently, the echo model of a radar target partially covered with a TMM is developed, which extends the model of ISAR jamming with TMM fully covering to a more general and near-realistic case in this letter. Then, the echoes of each component of the target are obtained by electromagnetic simulation, and the time-varying reflection phase of the 1-bit TMM is obtained by experimental testing. Finally, using the abovementioned data, we validate that ISAR image of the component covered metasurface can be blurred using random time modulation sequence. Meanwhile, duplicated components can be produced in the ISAR image using periodic time modulation sequence. Experimental results of range profile jamming confirm the validity of the conclusions in this letter. The partial defocusing or duplicating of the radar target in the ISAR image can reduce the recognized possibility and enhance the jamming performance, effectively.

Photonic super-resolution millimeter-wave joint radar-communication system using self-coherent detection.

A millimeter-wave (MMW) joint radar-communication (JRC) system with super-resolution is proposed and experimentally demonstrated, using optical heterodyne upconversion and self-coherent detection downconversion techniques. The point lies in the designed coherent dual-band constant envelope linear frequency modulation-orthogonal frequency division multiplexing (LFM-OFDM) signal with opposite phase modulation indexes for the JRC system. Then the self-coherent detection, as a simple and low-cost means, is accordingly facilitated for both de-chirping of MMW radar and frequency downconversion reception of MMW communication, which circumvents costly high-speed mixers along with MMW local oscillators and, more significantly, achieves the real-time decomposition of radar and communication information. Furthermore, a super-resolution radar range profile is realized through the coherent fusion processing of dual-band JRC signals. In experiments, a dual-band LFM-OFDM JRC signal centered at 54 GHz and 61 GHz is generated. The two bands feature an identical instantaneous bandwidth of 2 GHz and carry an OFDM signal of 1 Gbaud, which helps to achieve a 6-Gbit/s data rate for communication and a 1.76-cm range resolution for radar.

A theoretical approach to improving interspecies welfare comparisons

The number of animals bred, raised, and slaughtered each year is on the rise, resulting in increasing impacts to welfare. Farmed animals are also becoming more diverse, ranging from pigs to bees. The diversity and number of species farmed invite questions about how best to allocate currently limited resources towards safeguarding and improving welfare. This is of the utmost concern to animal welfare funders and effective altruism advocates, who are responsible for targeting the areas most likely to cause harm. For example, is tail docking worse for pigs than beak trimming is for chickens in terms of their pain, suffering, and general experience? Or are the welfare impacts equal? Answering these questions requires making an interspecies welfare comparison; a judgment about how good or bad different species fare relative to one another. Here, we outline and discuss an empirical methodology that aims to improve our ability to make interspecies welfare comparisons by investigating welfare range, which refers to how good or bad animals can fare. Beginning with a theory of welfare, we operationalize that theory by identifying metrics that are defensible proxies for measuring welfare, including cognitive, affective, behavioral, and neuro-biological measures. Differential weights are assigned to those proxies that reflect their evidential value for the determinants of welfare, such as the Delphi structured deliberation method with a panel of experts. The evidence should then be reviewed and its quality scored to ascertain whether particular taxa may possess the proxies in question to construct a taxon-level welfare range profile. Finally, using a Monte Carlo simulation, an overall estimate of comparative welfare range relative to a hypothetical index species can be generated. Interspecies welfare comparisons will help facilitate empirically informed decision-making to streamline the allocation of resources and ultimately better prioritize and improve animal welfare.

Radar HRRP Open Set Target Recognition Based on Closed Classification Boundary

Radar automatic target recognition based on high-resolution range profile (HRRP) has become a research hotspot in recent years. The current works mainly focus on closed set recognition, where all the test samples are assigned to the training classes. However, radar may capture many unknown targets in practical applications, and most current methods are incapable of identifying the unknown targets as the ’unknown’. Therefore, open set recognition is proposed to solve this kind of recognition task. This paper analyzes the basic classification principle of both recognitions and makes sure that determining the closed classification boundary is the key to addressing open set recognition. To achieve this goal, this paper proposes a novel boundary detection algorithm based on the distribution balance property of k-nearest neighbor objects, which can be used to realize the identification of the known and unknown targets simultaneously by detecting the boundary of the known classes. Finally, extensive experiments based on measured HRRP data have demonstrated that the proposed algorithm is indeed helpful to greatly improve the open set performance by determining the closed classification boundary of the known classes.