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Статті в журналах з теми "Spectral Doppler analysis"

Автор: Grafiati

Опубліковано: 10 березня 2023

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1

Parkinson, M. L., K. M. Hannah, and P. L. Dyson. "Complexity in the high latitude HF radar spectral width boundary region." Annales Geophysicae 26, no. 4 (May 13, 2008): 877–92. http://dx.doi.org/10.5194/angeo-26-877-2008.

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Abstract. SuperDARN radars are sensitive to the collective Doppler characteristics of decametre-scale irregularities in the high latitude ionosphere. The radars routinely observe a distinct transition from large spectral width (>100 m s−1) located at higher latitudes to low spectral width (<50 m s−1) located at lower latitudes. Because of its equatorward location, the TIGER Tasmanian radar is very sensitive to the detection of the spectral width boundary (SWB) in the nightside auroral ionosphere. An analysis of the line-of-sight velocities and 2-D beam-swinging vectors suggests the meso-scale (~100 km) convection is more erratic in the high spectral width region, but slower and more homogeneous in the low spectral width region. The radar autocorrelation functions are better modelled using Lorentzian Doppler spectra in the high spectral width region, and Gaussian Doppler spectra in the low spectral width region. However, paradoxically, Gaussian Doppler spectra are associated with the largest spectral widths. Application of the Burg maximum entropy method suggests the occurrence of double-peaked Doppler spectra is greater in the high spectral width region, implying the small-scale (~10 km) velocity fluctuations are more intense above the SWB. These observations combined with collective wave scattering theory imply there is a transition from a fast flowing, turbulent plasma with a correlation length of velocity fluctuations less than the scattering wavelength, to a slower moving plasma with a correlation length greater than the scattering wavelength. Peak scaling and structure function analysis of fluctuations in the SWB itself reveals approximately scale-free behaviour across temporal scales of ~10 s to ~34 min. Preliminary scaling exponents for these fluctuations, αGSF=0.18±0.02 and αGSF=0.09±0.01, are even smaller than that expected for MHD turbulence.

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2

Hayashi, Nobuharu, Yukio Miyamoto, Norio Nakata, Takeo Irie, Masahiro Ikegami, Keiko Asao, and Shimpei Tada. "Breast masses: Color Doppler, power Doppler, and spectral analysis findings." Journal of Clinical Ultrasound 26, no. 5 (June 1998): 231–38. http://dx.doi.org/10.1002/(sici)1097-0096(199806)26:5<231::aid-jcu1>3.0.co;2-d.

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3

Chaxel, Y., E. M. Griffin, and N. P. Meredith. "Spectral analysis techniques for doppler lidar measurements." Advances in Space Research 21, no. 10 (January 1998): 1441–44. http://dx.doi.org/10.1016/s0273-1177(97)00657-1.

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4

Anandan, V. K., C. J. Pan, T. Rajalakshmi, and G. Ramachandra Reddy. "Multitaper spectral analysis of atmospheric radar signals." Annales Geophysicae 22, no. 11 (November 29, 2004): 3995–4003. http://dx.doi.org/10.5194/angeo-22-3995-2004.

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Abstract. Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST) radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.

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5

Herment, A., and J. F. Giovannelli. "An Adaptive Approach to Computing the Spectrum and Mean Frequency of Doppler Signals." Ultrasonic Imaging 17, no. 1 (January 1995): 1–26. http://dx.doi.org/10.1177/016173469501700101.

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Анотація:

Modern ultrasound Doppler systems are facing the problem of processing increasingly shorter data sets. Spectral analysis of the strongly nonstationary Doppler signal needs to shorten the analysis window while maintaining a low variance and high resolution spectrum. Color flow imaging requires estimation of the Doppler mean frequency from even shorter Doppler data sets to obtain both a high frame rate and high spatial resolution. We reconsider these two estimation problems in light of adaptive methods. A regularized parametric method for spectral analysis as well as an adapted mean frequency estimator are developed. The choice of the adaptive criterion is then addressed and adaptive spectral and mean frequency estimators are developed to minimize the mean square error on estimation in the presence of noise. Two suboptimal spectral and mean-frequency estimators are then derived for real-time applications. Finally, their performance is compared to that of both the FFT based periodogram and the AR parametric spectral analysis for the spectral estimator, and, to both the correlation angle and the Kristoffersen's [8] estimators for the mean frequency estimator using Doppler data recorded in vitro.

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6

Burns, Peter N. "The physical principles of Doppler and spectral analysis." Journal of Clinical Ultrasound 15, no. 9 (November 1987): 567–90. http://dx.doi.org/10.1002/jcu.1870150903.

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7

Mahieddine, Latfaoui, and Bereksi Reguig Fethi. "Time Frequency Analysis of Femoral Doppler Ultrasound Signals by AR Modelling." Applied Mechanics and Materials 302 (February 2013): 319–25. http://dx.doi.org/10.4028/www.scientific.net/amm.302.319.

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In this study, we have compared the efficiency of the short time Fourier transform (STFT) and autoregressive modelling (AR) and autoregressive moving average (ARMA) of the femoral Doppler artery ultrasonic signals, in order to determine the spectral broadening index (SBI). Our aim is to detect the impact of the two modelling approaches on sonograms and of power spectral density- frequency diagrams obtained from femoral arterial Doppler Signals. The sonograms have been then used to compare the methods in terms of their frequency resolution and effects in determining the stenosis of femoral artery. In this paper we have used generated frequency envelopes from the Doppler spectrum to determine an index showing the degree of severity of stenosis cases. This index called broadening spectral index is calculated for various real cases.

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8

Formosa, Cynthia, Christian Ellul, Anabelle Mizzi, Stephen Mizzi, and Alfred Gatt. "Interrater Reliability of Spectral Doppler Waveform." Journal of the American Podiatric Medical Association 108, no. 4 (July 1, 2018): 280–84. http://dx.doi.org/10.7547/16-026.

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Background: Spectral Doppler ultrasound examination of pedal arteries is one of the most frequently used noninvasive assessment methods by health-care professionals for the diagnosis and ongoing monitoring of people at risk for or living with peripheral arterial disease. The aim of this study was to determine the interrater reliability of the interpretation of spectral Doppler waveform analysis. Methods: An interrater reliability study was conducted among five experienced podiatric physicians at the University of Malta Research Laboratory (Msida, Malta). A researcher who was not a rater in this study randomly selected 229 printed spectral Doppler waveforms from a database held at the University of Malta. Each rater independently rated the qualitative spectral waveforms. Results: Interrater reliability of the spectral Doppler waveform interpretation was excellent among the five experienced podiatric physicians (α = 0.98). The intraclass correlation coefficient showed a high degree of correlation in waveform interpretation across raters (P < .001). Conclusions: This study demonstrates high interrater reliability in visual spectral Doppler interpretation among experienced clinicians. The current foot screening guidelines do not refer to spectral Doppler waveform analysis in their recommendations, which has been shown in studies to be an important modality for the diagnosis of peripheral arterial disease when ankle-brachial pressure indexes are falsely elevated in calcified arteries. If interpreted correctly, the information obtained can provide an indication of the presence of peripheral arterial disease and facilitate early management of this condition.

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9

Sheppard, Brian E., Merhala Thurai, Peter Rodriguez, Patrick C. Kennedy, and David R. Hudak. "Improved Precipitation Typing Using POSS Spectral Modal Analysis." Journal of Atmospheric and Oceanic Technology 38, no. 3 (March 2021): 537–54. http://dx.doi.org/10.1175/jtech-d-20-0075.1.

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AbstractThe Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar that measures the Doppler velocity spectra from precipitation falling in a small volume near the sensor. The sensor records a 2D frequency of occurrence matrix of the velocity and power at the mode of each spectrum measured over 1 min. The centroid of the distribution of these modes, along with other spectral parameters, defines a data vector input to a multiple discriminant analysis (MDA) for classification of the precipitation type. This requires the a priori determination of a training set for different types, particle size distributions (PSDs), and wind speed conditions. A software model combines POSS system parameters, a particle scattering cross section, and terminal velocity models, to simulate the real-time Doppler signal measured by the system for different PSDs and wind speeds. This is processed in the same manner as the system hardware to produce bootstrap samples of the modal centroid distributions for the MDA training set. MDA results are compared to images from the Multi-Angle Snowflake Camera (MASC) at the MASCRAD site near Easton, Colorado, and to the CSU–CHILL X-band radar observations from Greeley, Colorado. In the four case studies presented, POSS successfully identified precipitation transitions through a range of types (rain, graupel, rimed dendrites, aggregates, unrimed dendrites). Also two separate events of hail were reported and confirmed by the images.

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10

Gergely, Mathias, Maximilian Schaper, Matthias Toussaint, and Michael Frech. "Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes." Atmospheric Measurement Techniques 15, no. 24 (December 20, 2022): 7315–35. http://dx.doi.org/10.5194/amt-15-7315-2022.

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Abstract. This study explores the potential of using Doppler (power) spectra from vertically pointing C-band radar birdbath scans to investigate precipitating clouds above the radar. First, the new birdbath scan strategy for the network of dual-polarization C-band radars operated by the German Meteorological Service (Deutscher Wetterdienst, DWD) is outlined, and a novel spectral postprocessing and analysis method is presented. The postprocessing algorithm isolates the weather signal from non-meteorological contributions in the radar output based on polarimetric attributes, identifies the statistically significant precipitation modes contained in each Doppler spectrum, and calculates characteristics of every precipitation mode as well as multimodal properties that describe the relation among different modes when more than a single mode is identified. To achieve a high degree of automation and flexibility, the postprocessing chain combines classical signal processing with clustering algorithms. Uncertainties in the calculated modal and multimodal properties are estimated from the small variations associated with smoothing the measured radar signal. The analysis of five birdbath scans recorded at different radar sites and for various precipitation conditions delivers reliable profiles of the derived modal and multimodal properties for two snowfall cases and for stratiform precipitation above and below the melting layer. To help identify the dominant precipitation growth mechanism, Doppler spectra from DWD's birdbath scans can be used to retrieve the typical degree of riming for individual snow modes. Here, the automatically identified snow modes span a wide range of riming conditions with estimated rime mass fractions (RMFs) of up to RMF>0.5. The evaluation of Doppler spectra inside the melting layer and for an intense frontal shower, with observed radar reflectivities of up to about 40 dBZ, occasionally shows erroneously identified precipitation modes and spurious results for the calculated higher-order Doppler moments of skewness and kurtosis. Nonetheless, the Doppler spectra from DWD's operational C-band radar birdbath scan provide a detailed view into the precipitating clouds and allow for calculating a high-resolution profile of radar reflectivity, mean Doppler velocity, and spectral width even in intense frontal precipitation.

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11

Chammas, Maria Cristina, Renê Gerhard, Ilka Regina Souza De Oliveira, Azzo Widman, Nestor De Barros, Marcelo Durazzo, Alberto Ferraz, and Giovanni Guido Cerri. "Thyroid nodules: Evaluation with power Doppler and duplex Doppler ultrasound." Otolaryngology–Head and Neck Surgery 132, no. 6 (June 2005): 874–82. http://dx.doi.org/10.1016/j.otohns.2005.02.003.

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This study purposes a new classification of thyroid nodules blood flow by power duplex Doppler ultrasound. A total of 177 nodules were studied with B-mode scanning, power Doppler, and spectral analysis. These data were compared with cytological results from ultrasound-guided fine-needle aspiration biopsy. Univariate and multivariate logistic regression analysis were performed. The power Doppler analysis of the nodules produced 5 vascular patterns: I, absence of signal blood flow; II, exclusively perinodular blood flow; III, perinodular > central blood flow; IV, central blood flow > perinodular blood flow; V, exclusively central blood flow. Statistical analysis revealed a significant relationship between these vascular patterns and cytological results. The spectral analysis demonstrated that the resistance index were higher in nodules with malignant versus other cytology ( P >0.001). The results indicate that power duplex Doppler facilitates screening of thyroid nodules at high risk for malignancy with elevated sensitivity (92.3%) and specificity (88%).

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12

Hudson, Judith A., Susan T. Finn-Bodner, Joan R. Coates, Donald C. Sorjonen, Stephen T. Simpson, James C. Wright, Jan E. Steiss, et al. "COLOR DOPPLER AND DOPPLER SPECTRAL ANALYSIS IN THE SPINAL CORD OF NORMAL DOGS." Veterinary Radiology Ultrasound 36, no. 6 (November 1995): 542–47. http://dx.doi.org/10.1111/j.1740-8261.1995.tb00309.x.

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13

West, JNW, PJ Champion de Crespigny, and WA Littler. "Carotid Body Doppler Spectral Analysis: Correlation between Various Doppler Parameters and Baroreceptor Function." Clinical Science 75, s19 (December 1, 1988): 28P. http://dx.doi.org/10.1042/cs075028p.

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14

dos Reis, Gisele FM, Rodrigo B. Nogueira, Adriana C. Silva, Guilherme Oberlender, Ruthnéa AL Muzzi, and Matheus M. Mantovani. "Spectral analysis of femoral artery blood flow waveforms of conscious domestic cats." Journal of Feline Medicine and Surgery 16, no. 12 (April 9, 2014): 972–78. http://dx.doi.org/10.1177/1098612x14529123.

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The qualitative and quantitative aspects of femoral artery blood flow waveform spectra were evaluated in 15 male and 15 female Persian and mixed breed domestic cats ( Felis catus), which were healthy and not sedated, using duplex Doppler ultrasonography (DDU). Spectral Doppler demonstrated a biphasic characteristic in 16 (53.34%) of the animals evaluated, and a triphasic characteristic in the 14 (46.66%) remaining animals. The systolic blood pressure and heart rate values were within the normal range for the species. The quantitative parameters evaluated, based on the spectral Doppler, were as follows: systolic velocity peak (SVP), recent diastolic velocity peak (RDVP), end diastolic velocity peak (EDVP), mean velocity (MV), integral velocity time (ITV), artery diameter (AD), femoral flow volume (FFV), pulsatility index (PI), resistive index (RI), systolic peak acceleration time (AT) and deceleration time (DT). The respective mean values were: 36.41 ± 7.33 cm/s, 4.69 ± 0.90 cm/s, 10.74 ± 2.74 cm/s, 23.06 ± 4.86 cm/s, 3.91 ± 1.05 cm, 0.17 ± 0.04 cm, 0.11 ± 0.08 cm3, 3.85 ± 0.19, 1.40 ± 0.20, 39.84 ± 7.38 ms, and 114.0 ± 22.15 ms. No significant differences were found between males and females. The analyses carried out on the femoral artery flow spectrum obtained by DDU showed that it is easy to use and highly tolerated in non-sedated, healthy cats. It appears that DDU may be a useful diagnostic technique, but further studies are needed to evaluate how it compares with invasive telemetric methodology or high-definition oscillometric waveform analytic techniques.

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15

Zhu, Hong, Qingping Wang, Ning Tai, Jingjian Huang, and Naichang Yuan. "Statistical Analysis of High-Resolution Coherent Monopulse Radar Sea Clutter." International Journal of Antennas and Propagation 2017 (2017): 1–28. http://dx.doi.org/10.1155/2017/7471918.

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A statistical analysis that properly characterizes sea clutter processes is indispensable both for optimum detection algorithm design and for performance prediction problems in maritime surveillance applications. In this paper, we present the statistical analysis of experimental sea clutter data collected by a high-resolution coherent monopulse radar. First, we present the amplitude statistical analyses for these clutter data. The results show that the K, Pareto, and CIG distributions can each provide good fits to the clutter data for three channels of monopulse radar. The analyses on the variations of the K distribution parameters with range suggest that the scale parameter is closely associated with the clutter powers and that the shape parameter is influenced by the sea state. Then, we focus on the correlation properties. The averaged results suggest that the temporal and spatial correlation properties are similar for the clutter of all three channels. Moreover, the clutter between the sum and difference channels is almost completely correlated in elevation and is lowly correlated in azimuth. Finally, we perform a spectral analysis, highlighting the temporal and spatial variabilities of Doppler spectra. It is found that the individual Doppler spectra in all three channels can be represented by Gaussian-shaped power spectral densities, and their centroid and width can be modeled as two separate stage linear functions of spectrum intensity.

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16

Hysell, D. L., G. Michhue, M. F. Larsen, R. Pfaff, M. Nicolls, C. Heinselman, and H. Bahcivan. "Imaging radar observations of Farley Buneman waves during the JOULE II experiment." Annales Geophysicae 26, no. 7 (July 3, 2008): 1837–50. http://dx.doi.org/10.5194/angeo-26-1837-2008.

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Abstract. Vector electric fields and associated E×B drifts measured by a sounding rocket in the auroral zone during the NASA JOULE II experiment in January 2007, are compared with coherent scatter spectra measured by a 30 MHz radar imager in a common volume. Radar imaging permits precise collocation of the spectra with the background electric field. The Doppler shifts and spectral widths appear to be governed by the cosine and sine of the convection flow angle, respectively, and also proportional to the presumptive ion acoustic speed. The neutral wind also contributes to the Doppler shifts. These findings are consistent with those from the JOULE I experiment and also with recent numerical simulations of Farley Buneman waves and instabilities carried out by Oppenheim et al. (2008). Simple linear analysis of the waves offers some insights into the spectral moments. A formula relating the spectral width to the flow angle, ion acoustic speed, and other ionospheric parameters is derived.

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17

HOUGH, A. D., A. P. MOORE, and M. P. JONES. "Peripheral Nerve Motion Measurement with Spectral Doppler Sonography: A Reliability Study." Journal of Hand Surgery 25, no. 6 (December 2000): 585–89. http://dx.doi.org/10.1054/jhsb.2000.0453.

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This study evaluates single operator test-retest reliability of spectral Doppler ultrasound measurement of median nerve excursion during wrist extension. Longitudinal motion of the median nerve was measured at the elbow on three occasions in both upper limbs of 16 healthy subjects using a standard colour Doppler ultrasound system. The mean of the three maximum velocity time integrals was calculated from the spectral Doppler sonogram of each test. Analysis of data with intraclass correlation coeffcient indicated a high degree of repeatability (0.92). Spectral Doppler ultrasound may provide a valuable method for measurement of peripheral nerve motion and may have a role in the clinical assessment of entrapment syndromes.

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18

Moisseev, D. N., V. Chandrasekar, C. M. H. Unal, and H. W. J. Russchenberg. "Dual-Polarization Spectral Analysis for Retrieval of Effective Raindrop Shapes." Journal of Atmospheric and Oceanic Technology 23, no. 12 (December 1, 2006): 1682–95. http://dx.doi.org/10.1175/jtech1945.1.

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Abstract Dual-polarization radar observations of precipitation depend on size–shape relations of raindrops. There are several studies presented in literature dedicated to the investigation of this relation. In this work a new approach of investigating raindrop size–shape relation on short time and spatial scales from radar observations is presented. The presented method is based on the use of dual-polarization Doppler power spectral analysis. By measuring complete Doppler spectra at a sufficiently high elevation angle at two polarization settings, namely, horizontal and vertical, it is possible to retrieve drop size distribution (DSD) parameters, ambient air velocity, spectral broadening, and the slope of the assumed linear dependence of raindrop size–shape relation. This paper is mainly focused on the development of the retrieval algorithm and analysis of its performance. As a part of the proposed method an efficient algorithm for DSD parameter retrieval was developed. It is shown that the DSD parameter retrieval method, which usually requires the solution of five-parameter nonlinear optimization problems, can be simplified to a three-parameter nonlinear least squares problem. Furthermore, the performance of the proposed retrieval technique is illustrated on the dual-polarization measurements collected by the S-band Transportable Atmospheric Radar (TARA) at Cabauw, Netherlands, and by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar from Greeley, Colorado.

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19

Hudson, Judith A., Donald F. Buxton, Nancy R. Cox, Susan T. Finn-Bodner, Stephen T. Simpson, James C. Wright, Shellie S. Wallace, and Alexander Mitro. "COLOR FLOW DOPPLER IMAGING AND DOPPLER SPECTRAL ANALYSIS OF THE BRAIN OF NEONATAL DOGS." Veterinary Radiology Ultrasound 38, no. 4 (July 1997): 313–22. http://dx.doi.org/10.1111/j.1740-8261.1997.tb00861.x.

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20

Wang, Yadong, Tian-You Yu, Alexander V. Ryzhkov, and Matthew R. Kumjian. "Application of Spectral Polarimetry to a Hailstorm at Low Elevation Angle." Journal of Atmospheric and Oceanic Technology 36, no. 4 (April 2019): 567–83. http://dx.doi.org/10.1175/jtech-d-18-0115.1.

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AbstractSpectral polarimetry has the potential to be used to study microphysical properties in relation to the dynamics within a radar resolution volume by combining Doppler and polarimetric measurements. The past studies of spectral polarimetry have focused on using radar measurements from higher elevation angles, where both the size sorting from the hydrometeors’ terminal velocities and polarimetric characteristics are maintained. In this work, spectral polarimetry is applied to data from the 0° elevation angle, where polarimetric properties are maximized. Radar data collected by the C-band University of Oklahoma Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) during a hailstorm event on 24 April 2011 are used in the analysis. The slope of the spectral differential reflectivity exhibits interesting variations across the hail core, which suggests the presence of size sorting of hydrometeors caused by vertical shear in a turbulent environment. A nearby S-band polarimetric Weather Surveillance Radar-1988 Doppler (KOUN) is also used to provide insights into this hailstorm. Moreover, a flexible numerical simulation is developed for this study, in which different types of hydrometeors such as rain and melting hail can be considered individually or as a combination under different sheared and turbulent conditions. The impacts of particle size distribution, shear, turbulence, attenuation, and mixture of rain and melting hail on polarimetric spectral signatures are investigated with the simulated Doppler spectra and spectral differential reflectivity.

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21

Gaiani, S., A. M. Casali, C. Serra, N. Venturoli, F. Piscaglia, L. Gramantieri, and L. Bolondi. "Doppler tissue characterization of small hepatic tumors. Comparison between doppler spectral analysis and color-power doppler flow imaging." European Journal of Ultrasound 7 (February 1998): S29. http://dx.doi.org/10.1016/s0929-8266(97)80217-0.

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22

Yu, Tian-You, Ricardo Reinoso Rondinel, and Robert D. Palmer. "Investigation of Non-Gaussian Doppler Spectra Observed by Weather Radar in a Tornadic Supercell." Journal of Atmospheric and Oceanic Technology 26, no. 3 (March 1, 2009): 444–61. http://dx.doi.org/10.1175/2008jtecha1124.1.

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Abstract Radar Doppler spectra that deviate from a Gaussian shape were observed from a tornadic supercell on 10 May 2003, exhibiting features such as a dual peak, flat top, and wide skirt in the nontornadic region. Motivated by these observations, a spectral model of a mixture of two Gaussian components, each defined by its three spectral moments, is introduced to characterize different degrees of deviation from Gaussian shape. In the standard autocovariance method, a Gaussian spectrum is assumed and biases in velocity and spectrum width estimates may result if this assumption is violated. The impact of non-Gaussian weather spectra on these biases is formulated and quantified in theory and, consequently, verified using four experiments of numerical simulations. Those non-Gaussian spectra from the south region of the supercell are further examined and a nonlinear fitting algorithm is proposed to estimate the six spectral moments and compare to those obtained from the autocovariance method. It is shown that the dual-Gaussian model can better represent observed spectra for those cases. The authors’ analysis suggests that vertical shear may be responsible for the flat-top or the dual-peak spectra in the lower elevation of 0.5° and their transition to the single-peak and wide-skirt spectra in the next elevation scan of 1.5°.

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23

Alexopoulos, Vassilios, Stefanos Kollias, Philippe Leger, Henry Boccalon, and Zoltan Csiki. "Higher-order spectral analysis in laser-Doppler flowmetry signal processing." Technology and Health Care 7, no. 2-3 (June 1, 1999): 85–101. http://dx.doi.org/10.3233/thc-1999-72-301.

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24

Warde, David A., and Sebastian M. Torres. "The Autocorrelation Spectral Density for Doppler-Weather-Radar Signal Analysis." IEEE Transactions on Geoscience and Remote Sensing 52, no. 1 (January 2014): 508–18. http://dx.doi.org/10.1109/tgrs.2013.2241775.

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25

Russell, D., K. F. Lindegaard, P. Nakstad, R. Nyberg-Hansen, and K. G. Øygarden. "DETECTION OF CAROTID OCCLUSIVE DISEASE BY PULSED DOPPLER SPECTRAL ANALYSIS." Acta Neurologica Scandinavica 69, S98 (January 29, 2009): 297–98. http://dx.doi.org/10.1111/j.1600-0404.1984.tb02486.x.

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26

Paik, C. H., G. L. Cote, J. S. DePonte, and M. D. Fox. "Fast Hartley transforms for spectral analysis of ultrasound Doppler signals." IEEE Transactions on Biomedical Engineering 35, no. 10 (1988): 885–88. http://dx.doi.org/10.1109/10.7298.

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27

HAYAKAWA, SHINYA, HIDEMI GOTO, YOSHIKI HIROOKA, AKIHIRO ITOH, TOMOYUKI TAKI, YOSHIHIRO WATANABE, TETSUO HAYAKAWA, and YASUO NAITOH. "Colour Doppler-guided spectral analysis of gall-bladder wall flow." Journal of Gastroenterology and Hepatology 13, no. 2 (February 1998): 181–85. http://dx.doi.org/10.1111/j.1440-1746.1998.tb00635.x.

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28

Xiao-Jiao Tao, I. Claesson, and N. Grbic. "Narrowband acoustic Doppler volume backscattering signal .I. Evolutionary spectral analysis." IEEE Transactions on Signal Processing 50, no. 11 (November 2002): 2644–55. http://dx.doi.org/10.1109/tsp.2002.804097.

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29

Tortoli, P., G. Maines, and C. Atzeni. "Velocity Profile Reconstruction Using Ultrafast Spectral Analysis of Doppler Ultrasound." IEEE Transactions on Sonics and Ultrasonics 32, no. 4 (July 1985): 555–61. http://dx.doi.org/10.1109/t-su.1985.31630.

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30

van Son, Jacques A. M., Stefan H. Skotnicki, Wim N. van Asten, Otto Daniels, Henk J. van Lier, and Leon K. Lacquet. "Quantitative assessment of coarctation in infancy by Doppler spectral analysis." American Journal of Cardiology 63, no. 17 (May 1989): 1282–85. http://dx.doi.org/10.1016/0002-9149(89)90194-x.

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31

Dessr, S., A. Fort, C. Manfredi, and S. Rocchi. "Adaptive AR Model Order Estimation for Doppler Signals Spectral Analysis." IFAC Proceedings Volumes 27, no. 8 (July 1994): 701–6. http://dx.doi.org/10.1016/s1474-6670(17)47791-3.

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32

Wu, C. H., Y. L. Chang, W. C. Hsu, J. Y. Ko, T. S. Sheen, and F. J. Hsieh. "Usefulness of Doppler spectral analysis and power Doppler sonography in the differentiation of cervical lymphadenopathies." American Journal of Roentgenology 171, no. 2 (August 1998): 503–9. http://dx.doi.org/10.2214/ajr.171.2.9694484.

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33

Gaiani, S., A. M. Casali, C. Serra, F. Piscaglia, N. Venturoli, L. Gramantieri, M. Valgimigli, and L. Bolondi. "Tissue characterization of small hepatic tumors. Quantitative doppler spectral analysis vs. power doppler flow imaging." Journal of Hepatology 28 (1998): 92. http://dx.doi.org/10.1016/s0168-8278(98)80566-7.

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34

Kaluzynski, K., and T. Palko. "Effect of method and parameters of spectral analysis on selected indices of simulated Doppler spectra." Medical & Biological Engineering & Computing 31, no. 3 (May 1993): 249–56. http://dx.doi.org/10.1007/bf02458044.

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35

David, J. Y., S. A. Jones, and D. P. Giddens. "Modern spectral analysis techniques for blood flow velocity and spectral measurements with pulsed Doppler ultrasound." IEEE Transactions on Biomedical Engineering 38, no. 6 (June 1991): 589–96. http://dx.doi.org/10.1109/10.81584.

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36

Torres, Sebastián M., and David A. Warde. "Staggered-PRT Sequences for Doppler Weather Radars. Part I: Spectral Analysis Using the Autocorrelation Spectral Density." Journal of Atmospheric and Oceanic Technology 34, no. 1 (January 2017): 51–63. http://dx.doi.org/10.1175/jtech-d-16-0071.1.

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AbstractThe autocorrelation spectral density (ASD) was introduced as a generalization of the classical periodogram-based power spectral density (PSD) and as an alternative tool for spectral analysis of uniformly sampled weather radar signals. In this paper, the ASD is applied to staggered pulse repetition time (PRT) sequences and is related to both the PSD and the ASD of the underlying uniform-PRT sequence. An unbiased autocorrelation estimator based on the ASD is introduced for use with staggered-PRT sequences when spectral processing is required. Finally, the strengths and limitations of the ASD for spectral analysis of staggered-PRT sequences are illustrated using simulated and real data.

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37

Huang, Shuying, Zhiwei Kang, Jin Liu, and Xin Ma. "Accuracy Analysis of Spectral Velocimetry for the Solar Doppler Difference Navigation." IEEE Access 9 (2021): 78075–82. http://dx.doi.org/10.1109/access.2021.3079500.

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38

Maniewski, R., P. Leger, P. Lewandowski, A. Liebert, P. Bendayan, H. Boccalon, L. Bajorski, and K. O. Möller. "Spectral analysis of laser-Doppler perfusion signal measured during thermal test." Technology and Health Care 7, no. 2-3 (June 1, 1999): 163–69. http://dx.doi.org/10.3233/thc-1999-72-307.

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39

Übeyli, Elif, Hakan Işık, and İnan Güler. "Application of FFT and Arma Spectral Analysis to Arterial Doppler Signals." Mathematical and Computational Applications 8, no. 3 (December 1, 2003): 311–18. http://dx.doi.org/10.3390/mca8030311.

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40

Yoo, S. J., J. Y. Min, and Y. H. Lee. "Normal pericardial fluid in the fetus: color and spectral Doppler analysis." Ultrasound in Obstetrics and Gynecology 18, no. 3 (September 2001): 248–52. http://dx.doi.org/10.1046/j.1469-0705.2001.00449.x.

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41

White, Brent, Sean Wessel, Weili Zheng, Daniel Gonzalez, Ali Sovari, Sreenivas Konda, and Leon Frazin. "Quantitative analysis of spectral Doppler clicks in assessment of aortic stenosis." Echocardiography 36, no. 12 (November 25, 2019): 2158–66. http://dx.doi.org/10.1111/echo.14541.

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42

Hall, Andrew F., Julia Bettlach, Scott P. Nudelman, and Sándor J. Kovács. "Echo machine-imposed limit on transmitral spectral Doppler velocity-profile analysis." Ultrasound in Medicine & Biology 23, no. 8 (January 1997): 1225–35. http://dx.doi.org/10.1016/s0301-5629(97)00124-5.

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43

Marini, Mario, Gregorio Lillo Odoardi, Giovanni Bolle, and Piero Tartaglia. "Duplex-doppler spectral analysis in the physiopathology of the temporomandibular joint." Computerized Medical Imaging and Graphics 18, no. 1 (January 1994): 35–43. http://dx.doi.org/10.1016/0895-6111(94)90059-0.

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44

Evtikhieva, O. A., V. I. Moskalevich, and N. M. Skornyakova. "Analysis of digital spectral processing of laser Doppler vibration meter signals." Measurement Techniques 49, no. 9 (September 2006): 907–12. http://dx.doi.org/10.1007/s11018-006-0210-9.

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45

Tortoli, P., G. Guidi, and P. Pignoli. "Transverse doppler spectral analysis for a correct interpretation of flow sonograms." Ultrasound in Medicine & Biology 19, no. 2 (January 1993): 115–21. http://dx.doi.org/10.1016/0301-5629(93)90003-7.

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46

Istok, Michael J., and Richard J. Doviak. "Analysis of the Relation Between Doppler Spectral Width and Thunderstorm Turbulence." Journal of the Atmospheric Sciences 43, no. 20 (October 1986): 2199–214. http://dx.doi.org/10.1175/1520-0469(1986)043<2199:aotrbd>2.0.co;2.

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47

Urban, G., M. J. Paidas, G. Bambi, F. Guidi, F. Mecacci, C. J. Lockwood, and P. Tortoli. "OC142: Multigate spectral Doppler analysis, new application in maternal-foetal science." Ultrasound in Obstetrics and Gynecology 24, no. 3 (August 2004): 255. http://dx.doi.org/10.1002/uog.1260.

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48

Herment, A. "Real-time spectral analysis of Doppler signals: A new parametric approach." Ultrasonic Imaging 11, no. 2 (April 1989): 147. http://dx.doi.org/10.1016/0161-7346(89)90063-1.

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49

AMINA, MELLE SEDDIK, and M. BEREKSI REGUIG FETHI. "ANALYSIS OF CAROTID ARTERIAL DOPPLER SIGNALS USING STFT AND WIGNER–VILLE DISTRIBUTION (WVD)." Journal of Mechanics in Medicine and Biology 09, no. 01 (March 2009): 49–62. http://dx.doi.org/10.1142/s0219519409002845.

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The study presented in this paper is concerned with the analysis of the ultrasound Doppler signal of the carotid arteries in the time-frequency domain using the short time Fourier transform (STFT) and the Wigner–Ville distribution (WVD). This study is carried out in order to investigate the behavior of the spectral broadening index (SBI) derived from spectra obtained using these methods. The variations in the shape of the Doppler power spectra as a function of time are presented in the form of sonograms in order to determine the degree of primitive carotid artery stenosis. The obtained results show a qualitative improvement in the appearance of the sonograms generated using the WVD over the STFT. However, despite this qualitative improvement the WVD suffers from some drawbacks: the presence of the cross terms which are primarily due to its quadratic nature. The application of the Choi–Williams distribution (CWD) in this analysis shows a noticeable reduction of these cross terms, improving therefore the quality of the sonograms. From these generated sonograms, the ultrasound frequency envelopes are extracted. The maximum and the mean frequencies in these envelopes are used to determine the SBI. The magnitude of the CWD-SBI is significantly greater than that of the STFT-SBI. In addition, there is a correlation between the SBIs obtained using the STFT and the CWD and the degree of severity of stenosis measured by 2D Doppler imaging.

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50

Latfaoui, M., and F. Bereksi Reguig. "Packets Wavelets and Stockwell Transform Analysis of Femoral Doppler Ultrasound Signals." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4212. http://dx.doi.org/10.11591/ijece.v8i6.pp4212-4220.

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<p>Ultrasonic Doppler signals are widely used in the detection of cardiovascular pathologies or the evaluation of the degree of stenosis in the femoral arteries. The presence of stenosis can be indicated by disturbing the blood flow in the femoral arteries, causing spectral broadening of the Doppler signal. To analyze these types of signals and determine stenosis index, a number of time-frequency methods have been developed, such as the short-time Fourier transform, the continuous wavelets transform, the wavelet packet transform, and the S-transform.</p>

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