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This paper introduces a novel waveform for wireless communication, denoted as Frequency-Modulated Orthogonal Frequency-Division Multiplexing (FM-OFDM). By frequency-modulating an OFDM signal and further defining a suitable cutoff subcarrier, the resulting constant-envelope waveform (ensuring a low Peak to Average Power Ratio) exhibits strong robustness not only to Doppler, but also to phase noise and carrier frequency offsets. These impairments introduce an additive error term at the information-bearing subcarriers that is mostly concentrated at the lowest part of the spectrum. No inter-carrier interference is thus present, and impairments can be easily overcome by mapping the information above a cutoff subcarrier. Theoretical expressions and numerical results prove the superiority of FM-OFDM over the state of the art, particularly in high-speed Rayleigh channels and/or high phase noise. This work was supported by the Spanish National Project IRENE-EARTH (PID2020-115323RB-C33/AEI/10.13039/501100011033)

The ambiguity problem of targets in Doppler beam sharpening (DBS) with forward-looking radar is considered. While DBS is proposed earlier to improve the angular resolution of the radar while keeping the antenna aperture size limited, such a solution suffers from ambiguities in the case of targets positioned symmetrically with respect to the platform movement. To address this problem, an approach named unambiguous Doppler-based forward-looking multiple-input multiple-output (MIMO) radar beam sharpening scan (UDFMBSC) is proposed, based on the combination of MIMO processing and DBS. The performance of the proposed method is compared to existing approaches using simulated data with point-like and extended targets. The method is successfully verified using experimental data.

We propose a strategy for magnetic navigation of collective stem cell microrobots in blood environments under ultrasound Doppler imaging. The cell microrobots are fabricated through a coculture process of stem cells and iron microparticles, they have spheroidal structures and are actuated under external magnetic fields. The collective cell microrobots can be reversibly gathered and spread by adjusting the magnetic interaction, and these microrobots are able to exhibit collective motion in whole blood under rotating magnetic fields. Simulation results indicate that the induced blood flow around the collective pattern affects the motion of red blood cells, and experimental results show that Doppler signals are observed when emitting ultrasound waves to the microrobots. Due to the induced three-dimensional blood flow, Doppler signals can also be observed when the imaging plane is above the collective microrobots, which enables indirect localization when performing navigation on uneven surfaces. Moreover, collective patterns of different numbers of microrobots are formed in flowing conditions, and these collective biohybrid agents are actively navigated against flowing blood with a flow rate up to 4.5 mL/min (mean velocity: 5.97 mm/s). Our study investigates a strategy for pattern formation and navigation of collective microrobots under ultrasound Doppler imaging, demonstrating the integration of collective control approach and medical imaging holds great potential for real-time active delivery tasks.

This article presents and experimentally evaluates a frequency error elimination technique suitable for unsynchronized bistatic Multiple-Input Multiple-Output (MIMO) radar for human-body detection. First, a mathematical expression of human-body localization using bistatic MIMO radar is presented. Then the direct path is used to eliminate the phase error created by the frequency difference between the transmitter and receiver. A new Doppler-shifted component of the MIMO channel without phase error is derived, and the locations of the multiple targets are calculated by the 2-dimensional MUltiple SIgnal Classification (MUSIC) method. Next, the results of simulations that examine frequency error versus power ratios are discussed to illustrate the effectiveness of the proposed method. An experiment is carried out in an indoor multipath-rich environment. To emulate the unsynchronized condition, the transmitter and receiver use independent Signal Generators (SGs). One to six targets are tested. The experiments demonstrate that our unsynchronized radar system can identify the locations of multiple targets with high accuracy.

Most left ventricular (LV) Doppler measurements vary significantly with age and gender, making it necessary to correct them for physiological variances. We aimed to verify the hypothesis that different Doppler measurements correlate nonlinearly with different biometric variables raised to different scaling factors and exponents. In this work, a total of 23 LV Doppler parameters were measured in 1224 healthy Chinese adults. An optimized multivariable allometric model (OMAM) and scaling equations were developed in 70% of the subjects (group A), and the reliability of the model and equations was verified using the remaining 30% of the subjects (group B) as well as 183 overweight subjects (group C). The single-variable isometric model (SVIM) with body surface area (BSA) as a scaling variable was used for comparison. Before correction, all 23 LV Doppler parameters correlated significantly with one or more of the biometric variables. In group B, gender differences were found in 47.8% (11/23) of the parameters and were eliminated in 81.8% (9/11) of the parameters after correction with OMAM. The successful correction rate with OMAM was 100% (23/23) in group B and 82.6% (19/23) in group C. New reference values for corrected Doppler measurements independent of biometric variables were established. The SVIM with BSA successfully corrected none of the 23 parameters. In conclusion, different LV Doppler parameters allometrically correlated with one or more of the biometric variables. The novel OMAM developed in this study successfully corrected the effects of the physiological variances of most biometric variables on Doppler measurements in healthy and overweight subjects, and was found to be far superior to the SVIM. However, whether the OMAM equations can be applied to other ethnicities, obese subjects, and pathological conditions requires further investigation.

This paper proposes a novel three-dimensional (3D) non-stationary irregular-shaped geometry-based stochastic model (IS-GBSM) for beyond fifth-generation (B5G) and sixth-generation (6G) vehicle-to-vehicle (V2V) millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) channels. By distinguishing dynamic clusters and static clusters, the proposed IS-GBSM for the first time explores the impact of vehicular traffic density (VTD) on channel statistics in B5G/6G V2V mmWave massive MIMO scenarios. Furthermore, a novel method is developed to model the channel space-time-frequency non-stationarity. In the developed method, dynamic/static correlated clusters are first generated by an improved K-Means clustering algorithm. Then, by employing a birth-death process based on correlated clusters, the consistency in birth and death between dynamic/static correlated clusters during time-array evolution is modeled. Key channel statistical properties, e.g., space-time-frequency correlation function (STF-CF) and Doppler power spectral density (DPSD), are derived. Simulation results demonstrate that the space-time-frequency non-stationarity is captured and the influence of VTDs on channel statistics is explored. Finally, the close agreement is achieved between simulation results and measurements, verifying the utility of proposed IS-GBSM.

This paper considers the localization of a stationary target using time delay and Doppler shift measurements obtained by moving monostatic sensors that takes the sensor motion during the localization period into consideration. Starting from the model equation of a previous work, we propose a new formulation of optimization through constrained weighted least-squares to solve for the target location by developing two new localization solutions, one in closed-form and the other by semi-definite relaxation. The new formulation enables the reduction of the minimum number of auxiliary variables in the closed-form solution and allows additional constraints in the SDR solution, resulting in fewer sensors needed in the former and less relaxation error and higher noise tolerance in the latter. Simulations validate the better performance of the proposed solutions than the previous ones.

Doppler ultrasound techniques are currently employed in several industrial, consumer, and biomedical applications. They are implemented in electronic systems of different complexity: from simple low-cost embedded boards to high-end echographs. The development, implementation, and periodic verification of such systems involve complex tests carried out through flow-rigs and phantoms. Unfortunately, these hydraulic circuits are affected by several issues, like the huge dimensions and the lack of an accurate reference for the velocity distribution developed by the fluid. In this work we present an innovative Flow Emulator Board (FEB). The FEB is compact and does not need moving fluids or pumps. Moreover, it produces a signal that mimics a programmable velocity profile with known characteristics. The FEB can replace the flow-rigs in most of the tests where Pulsed Wave Doppler (PWD) methods and PWD electronics systems are involved. The presented experiments show that the proposed FEB synthetizes arbitrary flow velocity profiles with programmable clutter, white noise, propagation attenuation, and sample volume extension; and show how FEB is employed for testing an industrial sensor and a research echograph.

This letter shows the first acquisition, Doppler tracking, and positioning results with Starlinks low Earth orbit (LEO satellite signals. A generalized likelihood ratio (GLR -based test is proposed to acquire Starlinks downlink signals. A Kalman filter (KF -based algorithm for tracking the Doppler frequency from the unknown Starlink signals is developed. Experimental results show Doppler tracking of six Starlink satellites, achieving a horizontal positioning error of 10 m.

In this paper, we present the methods to detect the channel delay profile and the Doppler spectrum of shallow underwater acoustic channels (SUAC). In our channel sounding methods, a short impulse in form of a sinusoid function is successively sent out from the transmitter to estimated the channel impulse response (CIR). A bandpass filter is applied to eliminate the interference from out-of-band (OOB). A threshould is utilized to obtain the maximum time delay of the CIR. Multipath components of the SUAC are specified by correlating the received signals with the transmitted sounding pulse with its shifted phases from 0 to 2Π. We show the measured channel parameters, which have been carried out in some lakes in Hanoi. The measured results illustrate that the channel is frequency selective for a narrow band transmission. The Doppler spectrum can be obtained by taking the Fourier transform of the time correlation of the measured channel transfer function. We have shown that, the theoretical maximum Doppler frequency fits well to that one obtained from measurement results.

The Third Sonic Boom Prediction Workshop was held on January 4–5, 2020, in conjunction with the AIAA SciTech conference. The workshop had 23 participants who represented 6 different countries and 1...

Objective: Carotid Doppler ultrasound has been a topic of recent interest, as it may be a promising noninvasive hemodynamic monitoring tool. In this study, the relation between carotid artery blood flow and invasive cardiac output (CO) was evaluated. Design: A prospective, observational study. Setting: A single-institution, tertiary referral hospital. Participants: Eighteen elective cardiac surgery patients. Interventions: CO was measured by calibrated pulse contour analysis. Simultaneously, carotid artery pulsed-wave Doppler measurements were obtained in the operating room in three clinical settings: after induction of anesthesia (T1), after a passive leg raise maneuverer (T2), and at the end of surgery (T3). Measurements and Main Results: Correlation and trending between carotid artery blood flow and invasive CO were evaluated. Furthermore, two Bland-Altman plots were constructed to evaluate the level of agreement between carotid artery-derived CO and invasive CO measurements. Carotid artery blood flow correlated moderately with invasive CO (ρ = 0.67, 95% confidence interval 0.56-0.76, p < 0.05). Concordance between the percentage change of carotid artery blood flow and invasive CO from T1 to T3 was 72%. The level of agreement between carotid artery-derived CO and invasive CO was ±2.29; ±2.57 L/min, with a bias of 0.1; –0.54 L/min, and mean error of 50% and 48%, for the two Bland-Altman analyses, respectively. Intraexamination precision was acceptable. Conclusions: In cardiac surgery patients, carotid artery blood flow correlated moderately with invasive CO measurements. However, the trending ability of carotid artery blood flow was poor, and carotid artery-derived CO tended not to be interchangeable with invasive CO.

In synthetic aperture imaging, the interpulse Doppler shift is commonly used, while the intrapulse Doppler shift is ignored. However, for the linear frequency modulation signal, the intrapulse Doppler shift can cause an additional range cell migration (ARCM) and a phase error term. Additionally, the ARCM may exceed a range resolution cell in certain cases of multireceiver synthetic aperture sonar (SAS), which will result in image defocus. Therefore, the intrapulse Doppler shift in multireceiver SAS should not be ignored in such cases. In this study, the condition of the negligible intrapulse Doppler shift is presented, that is, the moving distance of the sonar platform within a pulse should be much less than an azimuth resolution cell. Based on the multireceiver accurate time-delay model, a multireceiver SAS intrapulse Doppler shift signal model is developed by introducing the intrapulse Doppler frequency into the echo signal. After simplifying the accurate range history under the narrow-beam assumption, the range-Doppler spectrum is derived. Finally, a multireceiver SAS chirp scaling algorithm considering the intrapulse Doppler shift (IDS-CSA) is derived. The proposed algorithm can correct the ARCM and compensate the phase error (although not required), and then obtain a well-focused synthetic aperture image. The effectiveness of the proposed model and algorithm is verified by simulations and field data. The results show that the proposed algorithm provides a better image quality than the conventional multireceiver CSA when the condition of the negligible intrapulse Doppler shift is not met.

A theoretical sea echo modeling of the floating-platform high-frequency hybrid sky-surface wave radar (HSSWR) is presented. The ionosphere is considered to be a no-tilt reflecting plane moving in the vertical direction. Subsequently, the first-order sea clutter cross section with consideration of the platform sway and yaw motion is derived. Simulations are conducted to explore the influences of the ionospheric movement and the platform oscillation motion on the sea clutter power spectrum. Simulation results indicate that the platform sway motion may induce additional peaks that distribute symmetrically concerning the Bragg peaks, while the platform yaw motion and the ionospheric movement may broaden even split the sea clutter. Experiments are conducted with the newly-developed HSSWR system, of which the receiving arrays are simultaneously deployed on a floating platform and the shoreside. Experimental measurements concerning the frequency shift, Doppler width, and the arrival angle of the E-layer/F-layer ionosphere reflected direct wave are compared and analyzed. The study demonstrates the feasibility of the proposed modeling and provides valuable guidelines for the sea clutter characteristics analysis and the data quality assessments of the floating-platform HSSWR.

Time synchronization is the basis of coordination and cooperation in underwater acoustic networks. However, because of the propagation delay, node mobility, and Doppler shift, it is impossible to balance the accuracy and energy consumption simply in water. As a promising technology, partial clustering has high convergence and makes breakthroughs in time synchronization. This paper proposes PCDE-Sync, a novel synchronization mechanism with partial clustering and the Doppler effect. Firstly, a clustering method built on the artificial fish swarm algorithm is presented. It models the cluster construction according to fish's preying, swarming, and following behaviors. Secondly, we design a synchronization mechanism to conduct clock correction and compensation by the Doppler effect. Finally, we compare the performance of PCDE-Sync with the most advanced protocols, namely MU-Sync, MM-Sync, and DE-Sync, in terms of the cumulative error after synchronization, the mean square error under different clock skew and that under distinctive node mobility, and energy consumption. The experimental results show that PCDE-Sync makes a trade-off between accuracy and complexity, which does well in solving synchronization issues.

Underwater Acoustic Sensor Networks (UASNs) have been widely applied in marine monitoring, military reconnaissance, hydrology surveys, etc. Their location information is an important apriori knowledge when they are carried out underwater. However, the complex underwater environments impose great challenges on location acquisition, especially for Autonomous Underwater Vehicles (AUVs), because of their mobility and finite power. In UASNs, existing location and navigation methods can offer AUVs position information, but they may either need a Doppler Velocity Log (DVL), which is inefficient due to the complex underwater environments, or they may require additional localization infrastructure to deploy underwater, which suffers from large communication latency among AUVs, and costs enormous power. In this paper, an efficient Velocity Estimation and Location Prediction method (VELP) in underwater acoustic sensor networks is proposed to avoid the above restrictions. It only utilizes collaborations based on communication among AUVs to achieve higher-precision location with lower-cost. Specifically, we apply an AUV-assisted velocity estimation algorithm with Doppler Shift estimation in physical layer of UASNs, to improve the velocity estimation accuracy instead of the DVL. Meanwhile, we build a belief propagation-neural network-based location prediction model, which decreases the communication requirements and obviates introducing modeling errors. Extensive experimental results show VELP achieves superior performance on both accuracy and efficiency, demonstrating its great advantage in offering AUVs’ location information.

Recently, the long coherent accumulation of radar signals becomes relevant in the analysis of Doppler portraits of targets. This interest is related to the desire of researchers to obtain more information about radar purposes. Detailed spectral analysis provides additional information on the parameters of the target and its maneuvers. Some studies published in special articles are being discussed. They analyzed the methods of high resolution for the spectrums of refl ected signals. It is possible to obtain detailed Doppler portraits. The development of the elemental base of the construction of radar devices contributes to the improvement of the processing processes of refl ected signals. The possibilities of highlighting useful signals of small objects against the background of refl ections from the sea surface are considered. The article provides the results of processing signals recorded by radars made by the technology of digital antenna array. The experimental results of the Doppler portraits used a long-term coherent accumulation of signals in the L and X bands. Doppler portraits of ISS signals, Boeing-type passenger aircraft, MiG-29 fi ghter, helicopter are analyzed. The possibility of compensating for changes in the signal phase, which occurs during the radial acceleration of the ISS is shown. This allowed to increase the of signal-to-noise ratio to 6 dВ. Experimental results allow you to observe the maneuver of the target, to measure the acceleration of individual elements of the structure and their evolution. It is proposed to use the method of assessing Doppler portraits in the «radial speed - radial acceleration» coordinate system. The method is useful to use in radar surveillance systems of space objects, in the development of methods for recognizing classes of radar targets and in determining the number of objects in the target group. The development of this method of analysis of signals in prospective RADAR with the digital antenna array will help to solve problems of optimal signal processing, identify the number of targets in the group and maneuver the target, recognize classes of targets by the number of brilliant points and cross-Size targets.

When range ambiguity and range dependence coexist in forward-looking ground moving target indication (GMTI) radar, the traditional space-time adaptive processing (STAP) approaches may fail to work. To cope with this issue, a range-ambiguous clutter suppression approach based on elevation time diverse array (TDA) radar system and azimuth phase coding (APC) technique is presented in this paper. Due to the advantages of frequency scanning, the elevation TDA radar is able to cover all directions by transmitting a single time-shifted waveform. Therefore, a frequency bandpass filter is devised for each single range-bin to achieve the mainlobe echo extraction procedure. In the sequel, the azimuth phase decoding and Doppler filtering are performed to deal with the residual sidelobe ambiguous energy. With two-dimensional filtering, one can extract the unambiguous signals for each range region independently. Then, the traditional clutter compensation and STAP methods are employed to suppress the ground clutter. Finally, the effectiveness of the proposed framework in resolving range ambiguity are verified by the numerical simulation experiments.

Owing to the continuous random and non-periodic characteristics of the passive signal, the random range sidelobe coupling (RRSC) effects of the strong clutter (i.e., the direct path signal and the strong multipath signal) will exacerbate the performance of space-time adaptive processing (STAP) algorithm in airborne passive radar (APR). This paper analyzes the influence of RRSC caused by strong clutter on detection range cell of interest, and illustrates that strong clutter should be suppressed before applying the STAP algorithm. A cascaded least square algorithm (CLS) based on the directional dependence of clutter Doppler frequency is proposed for side-looking APR, where the first least square algorithm (LS) is performed to achieve the amplitude estimation of the Doppler-shift echo signal, and the channel amplitude and phase error correction factor (CF) can be obtained by the estimated amplitude information of the direct patch signal and the APR geometric configuration. The second LS is employed to further estimate the amplitude information of the strong clutter, and the resulting weight vector can be utilized for clutter cancellation. To make the CLS algorithm more practical, a batch version of the CLS (CLS-B) algorithm is proposed in this paper. The advantage of the method is that it cannot only cancel clutter along the clutter ridge, but also effectively prevent the suppression of targets falling in the clutter Doppler band. In addition, the proposed CLS algorithm performs well in the presence of the channel amplitude and phase error. A series of simulations are conducted to test the proposed algorithms.

International audience; A framework is proposed for long-term vehicular channel simulation based on the vector time-frequency autoregressive (VTFAR) model for a sparse parametric description of nonstationary multivariate random processes. Based on vehicle-to-infrastructure tunnel measurements, we estimate the VTFAR model parameters and validate the model by comparing the parametric and non-parametric spectra of the measured channel in terms of the delay spread and stationarity time. In addition, the VTFAR model stability is investigated and an approximation for the correlated scattering channel is proposed. The experimental validation shows a good agreement with RMSE of only 0.01 for the delay spread and 0.4 for the stationarity time. This approach provides an efficient alternative for non-stationary channel simulation that is measurement-based and computationally inexpensive.

Range/Doppler migration and velocity ambiguity are two well-known problems encountered in high-speed moving target detection using linear frequency-modulated continuous wave (LFMCW) automotive radar. To mitigate the problems, we introduce a simple Doppler-Range Processing (DRP) algorithm by first performing Doppler processing via fast Fourier transform (FFT) across slow-time samples, followed by a simple interpolation step, and then range processing via FFT along Doppler migration lines over fast-time samples. The proposed DRP algorithm can achieve full range and velocity resolutions, as well as full coherent integration gains. It attains a computational complexity comparable to that of the conventional 2D-FFT based Range-Doppler Processing (RDP) approach, computationally much more efficient than existing approaches. The proposed DRP algorithm can automatically resolve the velocity ambiguity problems. We analyze its velocity ambiguity mitigation capability in relation to the radar bandwidth and the number of slow-time samples within a Coherent Processing Interval (CPI). The effectiveness and the computational efficiency of the proposed algorithm are demonstrated by numerical examples.

Differs from conventional phased-array, frequency diverse array (FDA) employs a frequency increment across the array elements and thus produces a range-angle-dependent beampattern. This additional range dependence finds applications in target detection/localization, high-resolution synthetic aperture radar (SAR) imaging, and SAR deceptive jamming. To capture the essence behind those applications, we analyze the range, angle, and Doppler resolution capabilities of FDA radar signal via ambiguity function. As conventional ambiguity function is defined for a single-input single-output (SISO) signal, we extend it to the generalized ambiguity function for FDA radar signal, parameterized with the range, angle, and Doppler shifts of a target. Both theoretical analysis and numerical results show that the FDA radar with a large frequency increment has potentials in high-resolution ranging but will suffer from additional range ambiguity within the range bin and Doppler ambiguity. Moreover, the use of frequency increment brings FDA radar a virtual transmit aperture but decreases the directional gain.

The impulsive noise originated from regional lightning discharges can dramatically degrade the performance of skywave over-the-horizon radar (OTHR) target detection with generally 10-20-dB increase of noise level in the Doppler domain. As a result, it is necessary to excise impulsive noise in corrupted data while preserving the useful echo signal. Traditional techniques first locate the impulsive noise in slow-time data with a high-pass finite-duration impulse response (FIR) notch filter and then restore the contaminated samples by neighboring good data. However, the effect of impulsive noise is propagated into the subsequent filtered residuals, which will mislead the impulsive noise detection. Instead of the conventional detection-interpolation methods, we propose a novel impulsive noise excision approach based on robust smoothing. The proposed method can robustly smooth the corrupted data and determine the position of impulsive noise with a preset threshold against the residuals of corrupted data subtracting the smoothed signal. The contaminated data at last are replaced by the smoothed signal. Experimental results have demonstrated the effectiveness of our proposed method.

Pulsed wave (PW) Doppler ultrasound is routinely used in the clinic to assess blood flow. Our annual Doppler quality assurance tests revealed unexpectedly large errors in measurement of maximum velocity, exceeding our tolerance (error >20%), when using certain scanners with small Doppler sample volume dimensions. The aim of this study was to assess the dependence of maximum velocity estimates on PW Doppler sample volume size. A flow phantom with known steady flow was used to acquire maximum velocity estimates (maximum velocities of 24, 39 and 85 cm/s and sample volume range of 0.3–20 mm) with a variety of transducers and scanners in clinical use (51 probes from 4 manufacturers). Selected acoustic outputs were characterized using free-field hydrophone measurements. All maximum velocity estimates were within our tolerance for sample volume sizes ≥1.5 mm, although maximum velocity estimates typically increased with decreasing sample volume size. Errors exceeding our tolerance were commonly found for one manufacturer when using smaller sample volumes, resulting in up to 75% overestimation. Although intrinsic spectral broadening based on transit time considerations may help explain our findings, the sample volume dependence raises potential clinical concerns that users should be aware of and which manufacturers should consider addressing.

This letter proposes a new method for focusing ground maneuvering targets and estimating the motion parameters with a synthetic aperture radar (SAR) system. In this method, the Hough transform is applied to estimate the cross-track velocity from the slope of the range walk (RW) trajectory, and the RW and Doppler centroid shift are compensated. The second-order Keystone transform is performed to correct the additional range curve caused by the along-track velocity and cross-track acceleration. Then, we adopt the adaptive polynomial Fourier transform to estimate the second- and third-order Doppler parameters from a 1-D parameter interval, and the corresponding motion parameters are calculated. Finally, the moving target is well focused after the motion parameters compensation because the second- and third-order Doppler parameters are efficiently eliminated. Both the simulated and real data processing results are presented to demonstrate the validity of the proposed algorithm.

This paper deals with the problem of adaptive moving target detection, embedded in homogeneous Gaussian noise with unknown covariance matrix, for frequency diverse array multiple-input multiple-output (FDA-MIMO) radar operating in interference-dominant environment. Unlike traditional adaptive moving target detectors that need training data to estimate the jamming covariance matrix (JCM), we present the Rao and Wald test based adaptive detector, which requires no training data. Furthermore, we propose a two-stage approach to obtain maximum likelihood estimate (MLE) of the joint range, angle and Doppler, respectively. The corresponding signal-to-jamming-plus-noise ratio (SJNR) is derived to evaluate the FDA-MIMO radar performance. Simulation results show that the proposed detector outperforms the generalized likelihood ratio test (GLRT).

One of the challenges in ocean surface current retrieval from synthetic aperture radar (SAR) data is the estimation and removal of the wave-induced Doppler centroid (DC). This article demonstrates empirically the relationship between the dc derived from spaceborne X-band InSAR data and the ocean surface wind and waves. In this study, we analyzed over 300 TanDEM-X image pairs. It is found that the general characteristics of the estimated dc follow the theoretically expected variation with incidence angle, wind speed, and wind direction. An empirical geophysical model function (GMF) is fit to the estimated dc and compared to existing models and previous experiments. Our GMF is in good agreement (within 0.2 m/s) with other models and data sets. It is found that the wind-induced Doppler velocity contributes to the total Doppler velocity with about 15% of the radial wind speed. This is much larger than the sum of the contributions from the Bragg waves (~0.2 m/s) and the wind-induced drift current (~3% of wind speed). This indicates a significant (dominant) contribution of the long wind waves to the SAR dc. Moreover, analysis of dual-polarized data shows that the backscatter polarization ratio (PR=σ⁰VV/σ⁰HH) and the dc polarization difference (PD=|dcVV|-|dcHH|) are systematically larger than 1 and smaller than 0 Hz, respectively, and both increase in magnitude with incidence angle. The estimated PR and PD are compared to other theoretical and empirical models. The Bragg scattering theory-based (pure Bragg and composite surface) models overestimate both PR and PD, suggesting that other scattering mechanisms, e.g., wave breaking, are involved. In general, it is found that empirical models are more consistent with both backscatter and Doppler data than theory-based models. This motivates a further improvement of SAR dc GMFs.

Doppler shift measurement using time standard stations as passive radar beacons is well-established as a means of estimating virtual ionospheric height. A community science experiment in distributed Doppler shift measurement was conducted in October 2019 using the time station WWV, on the event of that station's centennial. Participants were asked to collect Doppler shift data from the WWV 5-MHz carrier via the open-source software program fldigi. This experiment garnered participation from stations across the country, demonstrating considerable volunteer interest: 45 recordings of WWV's 5-MHz beacon were collected. The novel element of this study is the use of distributed low-fidelity sensors in this geophysical domain, and the robust participation of the amateur radio community was enabled by inexpensive and readily available instrumentation. In this letter, we present an initial correlation analysis of the resultant data and discuss its implications for future long-term distributed Doppler networks. The data collected are in good agreement and, when examined together, offer some insights into regional trends. Despite the variety of equipment used by the amateur community, this community science approach shows promise for addressing the problem of undersampling in the geospace system.

Random stepped-frequency chirp waveform (RSFCW) is capable of achieving high-resolution synthetic aperture radar (SAR) imagery as well as certain electronic countermeasure capabilities. The Doppler-dependent phase incoherence due to the platform motion leads to degradation of the frequency synthesis of RSFCW. In this letter, a coherence processing algorithm for RSFCWSAR is developed with full cell Doppler correction (FCDC). The waveform structure of RSFCW is exploited to decompose the signal into different Doppler cells, which paves a way to the FCDC in phase alignment for frequency synthesis. Extensive simulation has confirmed the superiority of our method's performance in comparison to those of traditional techniques.

Parameter estimation is a problem of interest when designing new remote sensing instruments, and the corresponding lower performance bounds are a key tool to assess the performance of new estimators. In global navigation satellite systems reflectometry (GNSS-R), a noncoherent averaging is applied to reduce speckle and thermal noise, and subsequently the parameters of interest are estimated from the resulting waveform. This approach has been long regarded as suboptimal with respect to the optimal coherent one, which is true in terms of detection capabilities, but no analysis exists on the corresponding parameter estimation performance exploiting GNSS signals. First, we show that for certain signal models, both coherent and noncoherent Cramer-Rao bounds are equivalent, and therefore, any maximum likelihood estimation coherent/noncoherent combination scheme is efficient (optimal) at high signal-to-noise ratios. This is validated for an illustrative GNSS-R estimation problem. In addition, it is shown that considering the joint delay/Doppler/phase estimation problem, the noncoherent performance for the delay is still optimal, which is of practical importance for instance in altimetry applications.

Motion errors are inevitable in real-world scenarios and introduce significant phase errors in airborne synthetic aperture radar (SAR) imaging. Generally, these errors consist of the cross-coupling and spatially variant components. Cross-coupling errors can usually be eliminated by motion compensation (MoCo), whereas the latter are seldom addressed, which deteriorate the imaging qualities, especially for the high-resolution cases. To solve the problem, a novel approach based on 2-D range-Doppler expansion is proposed. First, an accurate range equation of the aircraft is obtained based on the inertial navigation system (INS) data. Then, the range-Doppler expansion corresponding to the slant range and Doppler centroid are performed, by which the echo signal is decoupled into two spatially variant parts in range and azimuth directions. Finally, the chirp-z transforms (CZTs) are employed to remove the range and azimuth spatial variations introduced, respectively, by the cross-track and along-track errors. Different from the conventional methods, our approach can greatly decrease the cross-coupling and spatially variant effects brought by motion errors in high-resolution cases. Computer simulation and real data experiments demonstrate the effectiveness of the proposed approach.

The broadening first-order sea clutters caused by the signals from different directions with various radial current velocities create severe disturbance for target detection using high-frequency surface wave radar (HFSWR). Conventional sea clutter suppression methods tend to remove the sea clutter and target signals when they are mixed in the Doppler spectrum. Based on the characteristics of the target signal and sea clutter in spatial-temporal domain, a new first-order sea clutter suppression method for HFSWR using orthogonal projection is proposed. The proposed method uses the data from multichannels and slow-time domain at the adjacent range cell to construct a covariance matrix, which can be used to obtain the sea clutter subspace by eigendecomposition. Later, original signals are projected onto the sea clutter subspace. Finally, subtract the component of the original signals in the sea clutter subspace from the original signals to achieve the suppression of sea clutter by retaining the target signals. The simulation and experimental results for a single target and multiple targets cases indicate that the proposed method can suppress the first-order sea clutter effectively, which enhances the target detection capacity in the sea clutter zone for HFSWR.

Background Impact on blood flow by double vein anastomosis in head and neck free flaps is unclear. We aimed to assess venous doppler loss of signal (LOS) rates of double vein system compared with a single vein system. Methods Consecutive free flaps with implanted venous flow couplers between 2015–2017 were included. LOS rates were compared between groups and with regard to flap type, defect site and recipient vein within double vein group. Results 92 double-vein (184 veins) and 48 single-vein flaps were included. LOS was similar in single- and double-vein flaps (11/48 (25%) versus 46/184 (25%), p = 0.765). Double veins had fewer flap takebacks compared with single vein (4.3% vs. 12.5%, p = 0.075). Common facial vein (CFV) anastomosis showed superior LOS rates compared with external jugular and CFV branches (p = 0.026). Conclusions Double vein anastomosis does not impact LOS rates, results in fewer flap takebacks, yet LOS rates depend on selected recipient vein.

For radar modeling and simulation of sea clutter, there are a number of key characteristics used to describe the observed features. These include the mean backscatter power, amplitude statistics, spatial and long-time temporal correlation, and the Doppler spectrum. Regarding the latter, a common modeling approach is to use the mean Doppler characteristics (width and center point) to relate to the sea conditions. However, this does not capture the time- and range-varying fluctuations of the Doppler spectra, which are important for assessing the behavior of coherent detection schemes. The evolving Doppler spectrum model offers a way to model these variations and can be described with a moderate number of parameters. Relating these to the observed geometry, environment and radar characteristics are important to make the models accessible. Previous work has characterized X-band radar sea clutter over a range of sea conditions and azimuth and grazing angles. In this article, new models are presented that capture variations with both the radar resolved area and integration time. This enables the evolved Doppler spectra model to be used over a much wider range of applications.

High-frequency surface wave radar (HFSWR) can be effectively used to detect ships in the exclusive economic zone. However, the ship signal is concealed and interfered with various clutter and background noise in the Doppler spectrum. In this letter, a range-Doppler (RD) image-based novel ship detection algorithm is proposed by exploiting spatial-frequency information and a unique feature fusion based on the analysis of variance. The algorithm subsumes three successive stages: Stage I--the plausible region of interest is captured, Stage II--the features from different sources are fused into one generalized feature space, and Stage III--an extreme learning machine-based classifier is utilized to localize the ships. Experimental results on challenging HFSWR-RD datasets demonstrate that the proposed algorithm has a competitive performance over other ship detection algorithms.

The rotating phased array radar (RPAR) has the potential to improve the capabilities of the current U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) operational network and can be more affordable than other candidate phased array radar (PAR) architectures that have been evaluated to replace the WSR-88D. Considering the demanding functional requirements for the future U.S. weather surveillance radar, it is expected that several advanced RPAR scanning techniques will need to be applied simultaneously to achieve them. In this letter, we present the integration of two such RPAR scanning techniques: motion-compensated steering (MCS) and distributed beams (DBs). MCS exploits beam agility to mitigate beam smearing, while DB exploits digital beamforming to reduce the scan time or the standard deviation (SD) of estimates. The integration of these techniques is demonstrated with the National Severe Storms Laboratory's (NSSL) dual-polarization advanced technology demonstrator (ATD) radar system. Results show that these techniques can be used simultaneously to enhance azimuthal resolution and reduce the SD of estimates without impacting data quality if certain obtainable tradeoff considerations are incorporated in the radar design process.

With the development of the radar sensing technology, hand gesture sensing and recognition has attracted much attention. This letter adopts a frequency-modulated continuous wave (FMCW) radar to achieve short-range hand gesture sensing and recognition. Specifically, the range, Doppler, and angle parameters of hand gestures are measured by fast Fourier transformation (FFT) and multiple signal classification (MUSIC) algorithm, respectively. The mixup (MP) algorithm combined with augmentation (AU) algorithm using a weight factor is applied to expand the hand gesture data. Then, a complementary multidimensional feature fusion network-based hand gesture recognition (CMFF-HGR) is designed to extract the features and achieve HGR. Finally, a series of experiments are carried out to verify the effectiveness of the proposed approach, and the results show that the recognition accuracy is higher than the existing alternatives with low computational complexity.

The application of Sentinel-1 interferometry to ice velocity measurements has until recently been limited by the significant horizontal scene motion associated with ice flow, which causes phase discontinuities (and associated unwrapping problems) at burst boundaries in Terrain Observation by Progressive Scans (TOPS) interferograms. Coregistering with a multiyear averaged external velocity mosaic based on offset-tracking can account for the bulk of the ice motion, but residual discontinuities sometimes remain, for example, due to seasonal variations in the ice velocity, or due to error sources such as azimuth shifts caused by ionospheric propagation. The presented method extends the external velocity coregistration with a local, spatially varying, coregistration in the burst overlap regions. This is based on the extended spectral diversity principle, which can only be applied in the overlap regions, but offers superior accuracy and resolution compared with traditional coregistration methods. The method considerably reduces phase discontinuities at burst boundaries, and potential new phase discontinuities at the overlap region edges are suppressed by an azimuth tapering of the applied coregistration shifts. An example scene is presented, and the phase discontinuities before and after application of the method are evaluated. The method is seen to remove phase discontinuities, with no adverse effects.

For Inverse Synthetic Aperture Radar (ISAR) imaging of maneuvering targets, the Doppler frequency induced by an arbitrary scatterer on the target is time-varying, and hence the traditional Range-Doppler (RD) algorithm is not appropriate for obtaining focusing ISAR images. In such a scenario, a novel ISAR technique, called range instantaneous Doppler derivatives (RIDD) algorithm has been recently proposed and two different kinds of well-focused ISAR images, named range Doppler centroid frequency (RDC) image and range Doppler frequency rate (RDR) image can be obtained. In order to improve the accuracy of the target classification and recognition, scaling approach for RIDD algorithm must be taken into consideration. In this paper, the point spread factor (PSF) representations and cross-range scaling factors of RDC image and RDR image obtained by RIDD algorithm are demonstrated analytically. On the basis of the PSFs and cross-range scaling factors, a novel imaging and scaling approach for RIDD algorithm in the presence of a low SNR environment based on Smoothed Integrated High-Resolution Time-Frequency-rate Representation (SIHR) combined with Coherent Integrated Smoothed Generalized Cubic Phase Function (CISCF) is proposed. As the proposed algorithm has high estimation accuracy and good antinoise capability, precise parameter estimation of the received signal can be achieved. Hence, high-quality scaled RDC and RDR images of the target can be reconstructed by the proposed approach. Experimental results of simulated data and real measured data verify the correctness of the PSF representations and demonstrate the effectiveness of the imaging and scaling approach proposed in this paper.

Deconvolution technique can be utilized in the forward-looking radar (FLR). However, the forward-looking imaging performance degenerates greatly due to the effect of high-speed movement of the platform. In this article, an efficient Bayesian forward-looking superresolution imaging algorithm based on Doppler deconvolution in expanded beam space is proposed. First, the Doppler phase information caused by the high-speed platform is fully exploited and the Doppler matrix is integrated with the antenna pattern. The Doppler convolution model of the echo signal for forward-looking is derived in this article. Then, the Doppler phase information is adopted to perform the Doppler deconvolution. Moreover, an expanded beam space is constructed to enhance the sparsity of the imaging scene. The complex Gaussian distribution and the Laplace distribution have been used to model the distribution characteristics of noise and targets in the imaging scene, respectively. Finally, based on the Bayesian framework, the forward-looking imaging problem is converted into the convex optimization problem. The performance assessment based on simulated and experimental data, also in comparison to the conventional real beam, truncated singular value decomposition (TSVD), iterative adaptive approach (IAA) methods, has demonstrated the effectiveness of our proposed algorithm under high-speed platform scenarios.

Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can image forward-looking terrain in the flight direction of the receiver. Current literature and reports about BFSAR mainly concentrate on the stationary scene and ground-moving target imaging. Unlike stationary and ground-moving targets, the translational and rotational movements of ship targets usually lead to complicated range cell migration (RCM) and Doppler frequency migration (DFM). Moreover, the characteristics of RCM and DFM for different scattering points of the ship target are significantly different, i.e., the characteristics of the RCM and DFM are 2-D spatial variation, ultimately leading to severe defocusing of ship target in the SAR image. To solve these problems, a kind of hybrid SAR-ISAR imaging formation is proposed for BFSAR ship target imaging. First, to solve the problem of the Doppler ambiguity caused by the forward-looking mode of the receiver, an efficient ambiguity estimation method based on the minimum entropy criterion is presented. Then, keystone transform and range alignment processing can be applied to correct the spatial variant range walk and higher order RCM, respectively. Moreover, in order to obtain a high-resolution and well-focused image after translational compensation, a new method based on the fractional Fourier transform (FrFT) and the Wigner-Ville distribution (WVD) is proposed, where FrFT is applied to separate the multiple main scattering points in each range cell, and WVD is applied to obtain the high-resolution time-frequency distribution of each scattering point. Compared with the conventional ISAR range-Doppler (RD) algorithm and time-frequency estimation-based imaging methods, this method not only has no cross terms but also has high processing accuracy and better antinoise performance.

Frequency-modulated continuous-wave (FMCW) radar is known for distance and velocity measurements of close and slow targets, i.e., targets with round-trip delays much shorter and Doppler periods much longer than the chirp repetition period. Solutions for distant targets have been presented for advanced FMCW radar architectures. Here, we analyze how a conventional homodyne I-channel FMCW radar can be used for a multitarget setting without the restrictions of close and slow targets. In a long-range setting, each target appears at two different ranges with opposite velocities. We develop a pure data processing solution to resolve this ambiguity and validate this approach through simulations and experimental results with a long-range moving test target. The work is motivated by our goal to use an off-the-shelf, low-power, and low-cost 24-GHz I-channel FMCW Doppler radar for continuous observation of volcanic eruptions and pyroclastic flows. These targets are moving at high speed and, for safety reasons, can only be observed from a greater distance, requiring the high-velocity long-range solution.