Статті в журналах: "Doppler Signals"

1

Fengzhen, Zhang, Li Guijuan, Zhang Zhaohui, and Hu Chen. "Doppler shift extraction of wideband signal using spectrum scaling matching." MATEC Web of Conferences 208 (2018): 01001. http://dx.doi.org/10.1051/matecconf/201820801001.

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Doppler shift is an important feature of moving targets. It can be used to extract target velocity, distance, track and other movement parameters. According to the problem of extracting Doppler shift for wideband signals with unstable line spectrum or no line spectrum, we proposed a Doppler shift extraction method for wideband signals based on spectral scaling matching. Firstly, a spectrum reference matrix corresponding to different relative Doppler shift is generated. Then, the matching degree of Doppler signal spectrum and reference matrix is measured by linear correlation coefficient. Finally, the Doppler shift of wideband signals is extracted through matching degree optimization. Simulation results show that the proposed method can extract the Doppler shift characteristics of wideband signals effectively.

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2

Li, Wenchao, Gangyao Kuang, and Boli Xiong. "Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD." Applied Sciences 8, no. 10 (October 2, 2018): 1801. http://dx.doi.org/10.3390/app8101801.

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Micro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals. As a time-frequency representation, the Hilbert-Huang transform (HHT) could extract the accurate instantaneous micro-Doppler signature from the radar signals by empirical mode decomposition and Hilbert transform. However, HHT has the shortcoming that it cannot decompose the signals with close-frequency components. To solve this problem, an innovative decomposition method for multicomponent micro-Doppler signals based on Hilbert–Huang transform and analytical mode decomposition (HHT-AMD) is proposed. In this method, the multicomponent micro-Doppler signals are firstly decomposed by empirical mode decomposition, and the decomposed signal components are transformed by Hilbert transform to get the Hilbert-Huang spectrum and marginal spectrum. Through the spectrum processing, we get the frequency distribution of each signal component. The next step is to judge whether there exists frequency aliasing in each signal component. If there is aliasing, the AMD method is used to decompose the signal until all the decomposed signals are mono-component signals. Evaluation considerations are covered with numerical simulations and experiments on measured radar data. The results demonstrate that compared with conventional HHT, the proposed method yields accurate decomposition for multicomponent micro-Doppler signals and improves the robustness of decomposition. The method presented here can also be applied in various settings of non-stationary signal analysis and filtering.

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3

Gong, Jiangkun, Jun Yan, Deren Li, and Deyong Kong. "Detection of Micro-Doppler Signals of Drones Using Radar Systems with Different Radar Dwell Times." Drones 6, no. 9 (September 19, 2022): 262. http://dx.doi.org/10.3390/drones6090262.

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Not any radar dwell time of a drone radar is suitable for detecting micro-Doppler (or jet engine modulation, JEM) produced by the rotating blades in radar signals of drones. Theoretically, any X-band drone radar system should detect micro-Doppler of blades because of the micro-Doppler effect and partial resonance effect. Yet, we analyzed radar data detected by three radar systems with different radar dwell times but similar frequency and velocity resolution, including Radar−α, Radar−β, and Radar−γ with radar dwell times of 2.7 ms, 20 ms, and 89 ms, respectively. The results indicate that Radar−β is the best radar for detecting micro-Doppler (i.e., JEM signals) produced by the rotating blades of a quadrotor drone, DJI Phantom 4, because the detection probability of JEM signals is almost 100%, with approximately 2 peaks, whose magnitudes are similar to that of the body Doppler. In contrast, Radar−α can barely detect any micro-Doppler, and Radar−γ detects weak micro-Doppler signals, whose magnitude is only 10% of the body Doppler’s. Proper radar dwell time is the key to micro-Doppler detection. This research provides an idea for designing a cognitive micro-Doppler radar by changing radar dwell time for detecting and tracking micro-Doppler signals of drones.

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4

Zhang, Shangbin, Qingbo He, Haibin Zhang, Kesai Ouyang, and Fanrang Kong. "Signal separation and correction with multiple Doppler acoustic sources for wayside fault diagnosis of train bearings." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 14 (March 22, 2016): 2664–80. http://dx.doi.org/10.1177/0954406216639342.

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The extraction of single train signal is necessary in wayside fault diagnosis because the acoustic signal acquired by a microphone is composed of multiple train bearing signals and noises. However, the Doppler distortion in the signal acquired by a microphone effectively hinders the signal separation and fault diagnosis. To address this issue, we propose a novel method based on the generalized S-transform, morphological filtering, and time–frequency amplitude matching-based resampling time series for multiple-Doppler-acoustic-source signal separation and correction. First, the original time–frequency distribution is constructed by applying generalized S-transform to the raw signal acquired by a microphone. Based on a morphological filter, several time–frequency distributions corresponding to different single source Doppler fault signals are extracted from the original time–frequency distribution. Subsequently, the time–frequency distributions are reverted to time signals by inverse generalized S-transform. Then, a resampling time series is built by time–frequency amplitude matching to obtain the correct signals without Doppler distortion. Finally, the bearing fault is diagnosed by the envelope spectrum of the correction signal. The effectiveness of this method is verified by simulated and practical signals.

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5

Grenier, N., F. Basseau, M. Rey, and L. LaGoarde-Segot. "Interpretation of Doppler signals." European Radiology 11, no. 8 (August 2001): 1295–307. http://dx.doi.org/10.1007/s003300100913.

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6

Zhang, Da, and Ranglei Liu. "Laser Doppler Signal Denoising Based on Wavelet Packet Thresholding Method." International Journal of Optics 2019 (November 14, 2019): 1–11. http://dx.doi.org/10.1155/2019/1097292.

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In laser Doppler velocimeter (LDV), calculation precision of Doppler shift is affected by noise contained in Doppler signal. In order to restrain the noise interference and improve the precision of signal processing, wavelet packet threshold denoising methods are proposed. Based on the analysis of Doppler signal, appropriate threshold function and decomposition layer number are selected. Heursure, sqtwolog, rigrsure, and minimaxi rules are adopted to get the thresholds. Processing results indicate that signal-to-noise ratio (SNR) and root mean square error (RMSE) of simulated signals with original SNR of 0 dB, 5 dB, and 10 dB in both low- and high-frequency ranges are significantly improved by wavelet packet threshold denoising. A double-beam and double-scattering LDV system is built in our laboratory. For measured signals obtained from the experimental system, the minimum relative error of denoised signal is only 0.079% (using minimaxi rule). The denoised waveforms of simulated and experimental signals are much more smooth and clear than that of original signals. Generally speaking, denoising effects of minimaxi and saqtwolog rules are better than those of heursure and rigrsure rules. As shown in the processing and analysis of simulated and experimental signals, denoising methods based on wavelet packet threshold have ability to depress the noise in laser Doppler signal and improve the precision of signal processing. Owing to its effectiveness and practicability, wavelet packet threshold denoising is a practical method for LDV signal processing.

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7

Dong, Shao Feng, Bao Qiang Du, and Wei Zhou. "Real-Time Measurement Method of Doppler Based on GPS Carrier Signals." Applied Mechanics and Materials 226-228 (November 2012): 2050–55. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.2050.

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According to Doppler effect of satellite on the time synchronization technology between satellite and the ground station, a real-time measurement method of Doppler is proposed based on GPS carrier signals. Using Doppler observations from GPS receiver, the method can real-timely measure Doppler frequency shift of GPS including dynamic Doppler and media Doppler whose error can be timely modified in the receiver end. Simulation results show that the frequency shift caused by dynamic Doppler, a main influencing factor in the course of transmission of time-frequency signal by GPS satellite, is between plus or minus several thousands Hz. Comparing to traditional measurement method of Doppler, the method makes it possible to fast track phase of signal in large dynamic range in synchronous technology.

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8

Jedelsky, Jan, Milan Maly, Ondrej Cejpek, Graham Wigley, and James F. Meyers. "Software-based processing system for phase Doppler systems." EPJ Web of Conferences 264 (2022): 01019. http://dx.doi.org/10.1051/epjconf/202226401019.

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A Monte Carlo simulation of Phase Doppler systems has been developed. It consists of three sections, the droplet flow description, generation of the photomultiplier signals and then their processing to determine droplet velocities and the time shift between the signals from the three scattered light detection apertures. With highly realistic Doppler bursts being simulated and processed, the question arises as to whether the signal processing software could be used to process ‘real-world’ experimental signals. In a preliminary assessment of its capabilities in such a situation, actual spray Doppler signals (from a Dantec fibre-based PDA system with a BSA signal processor) were recorded and used as input to the software signal processor. The signals from the three photomultipliers were input first into a Picoscope and then into the BSA processor. In this way droplet velocities and size estimates would be available from the BSA as control data. The signal outputs were taken as csv files, and input directly into the software signal processor. Initially the software determined the time location of the centre of each signal burst envelop. This approach was shown to measure signal delays from single cycle to multiple cycles. For this experiment, the software was modified by adding a zero-crossing approach to measure the single cycle delays. The introduction of this method should establish the accuracy of the complete software package in the real world as the results from the preliminary experiment show good agreement between the two techniques.

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9

Yan, Jun, Huiping Hu, Jiangkun Gong, Deyong Kong, and Deren Li. "Exploring Radar Micro-Doppler Signatures for Recognition of Drone Types." Drones 7, no. 4 (April 21, 2023): 280. http://dx.doi.org/10.3390/drones7040280.

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In this study, we examine the use of micro-Doppler signals produced by different blades (i.e., puller and lifting blades) to aid in radar-based target recognition of small drones. We categorize small drones into three types based on their blade types: fixed-wing drones with only puller blades, multi-rotor drones with only lifting blades, and hybrid vertical take-off and landing (VTOL) fixed-wing drones with both lifting and puller blades. We quantify the radar signatures of the three drones using statistical measures, such as signal-to-noise ratio (SNR), signal-to-clutter ratio (SCR), Doppler speed, Doppler frequency difference (DFD), and Doppler magnitude ratio (DMR). Our findings show that the micro-Doppler signals of lifting blades in all three drone types were stronger than those of puller blades. Specifically, the DFD and DMR values of pusher blades were below 100 Hz and 0.3, respectively, which were much smaller than the 200 Hz and 0.8 values for lifting blades. The micro-Doppler signals of the puller blades were weaker and more stable than those of the lifting blades. Our study demonstrates the potential of using micro-Doppler signatures modulated by different blades for improving drone detection and the identification of drone types by drone detection radar.

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10

Ericson, Mark A., and Lawrence L. Feth. "Detection of Doppler‐like signals." Journal of the Acoustical Society of America 103, no. 5 (May 1998): 3083. http://dx.doi.org/10.1121/1.422913.

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11

Opie, John C. "PTFE Grafts and Doppler Signals." Annals of Thoracic Surgery 40, no. 1 (July 1985): 100–101. http://dx.doi.org/10.1016/s0003-4975(10)61190-3.

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12

Luckman, N. P., J. M. Evans, R. Skidmore, J. D. Baker, and P. N. T. Wells. "Backscattered power in doppler signals." Ultrasound in Medicine & Biology 13, no. 10 (October 1987): L669—L670. http://dx.doi.org/10.1016/0301-5629(87)90069-x.

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13

Hoeks, Arnold P. G., Michael Hennerici, and Robert S. Reneman. "Spectral composition of doppler signals." Ultrasound in Medicine & Biology 17, no. 8 (January 1991): 751–60. http://dx.doi.org/10.1016/0301-5629(91)90157-r.

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14

Zhang, Lan, Xiao Mei Xu, Wei Feng, and You Gan Chen. "Doppler Estimation, Synchronization with HFM Signals for Underwater Acoustic Communications." Applied Mechanics and Materials 198-199 (September 2012): 1638–45. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1638.

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This paper presents the application of the hyperbolic frequency modulated (HFM) signal to acoustic propagation in order to improve the performance of underwater acoustic (UWA) communications. Due to the large delay spread caused by multipath propagation and the severe Doppler Effect of the channel, we propose the using of double HFM signals as preambles for Doppler estimation, frame synchronization in UWA communications. A theoretical analysis about Doppler-invariability of HFM signals was provided firstly, then some numerical simulations about Doppler estimation were implemented, and experiments on testing performance of double-HFM preambles for frame synchronization in the pool were carried out as well. The simulation and experimental results show that using double-HFM signals as preambles has the capability to take an explicit Doppler estimation and retiming for frame synchronization, demonstrating that it has a good prospect in underwater acoustic communication system, especially for moving platforms.

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15

Song, Nian Long, Da Zhang, and Qi Li. "Laser Doppler Velocimetry Signal Processing Based on Spectral Refinement and Correction." Advanced Materials Research 383-390 (November 2011): 6319–23. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6319.

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In order to improve the accuracy of signal processing in Laser Doppler Velocimetry, a method based on the association of spectral refinement and correction is presented. Zoom-FFT and ratio correction are adopted to realize this method. Basic principles of zoom-FFT and ratio correction are expounded. FFT and the method are adopted to process sinusoidal signals and simulated laser Doppler signals with different frequencies separately in circumstance of MATLAB 7.0. Comparisons between the results of FFT and the method are carried out. The comparisons show that this method has the capability to improve the accuracy of laser Doppler signal processing significantly and the operation time is acceptable for LDV system.

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16

Herr, Michael D., Cynthia S. Hogeman, Dennis W. Koch, Anandi Krishnan, Afsana Momen, and Urs A. Leuenberger. "A real-time device for converting Doppler ultrasound audio signals into fluid flow velocity." American Journal of Physiology-Heart and Circulatory Physiology 298, no. 5 (May 2010): H1626—H1632. http://dx.doi.org/10.1152/ajpheart.00713.2009.

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A Doppler signal converter has been developed to facilitate cardiovascular and exercise physiology research. This device directly converts audio signals from a clinical Doppler ultrasound imaging system into a real-time analog signal that accurately represents blood flow velocity and is easily recorded by any standard data acquisition system. This real-time flow velocity signal, when simultaneously recorded with other physiological signals of interest, permits the observation of transient flow response to experimental interventions in a manner not possible when using standard Doppler imaging devices. This converted flow velocity signal also permits a more robust and less subjective analysis of data in a fraction of the time required by previous analytic methods. This signal converter provides this capability inexpensively and requires no modification of either the imaging or data acquisition system.

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17

Ren, Sun, Zhang, and Zhao. "The Effect of Light Source Line Width on the Spectrum Resolution of Dual-Frequency Coherent Detection Signals." Sensors 19, no. 23 (November 29, 2019): 5264. http://dx.doi.org/10.3390/s19235264.

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In this paper, the power spectrum resolution problem of dual-frequency coherent mixing signals is analyzed when the Doppler frequency difference is small. The power spectrum function formula of the four optical coherent mixing signals is obtained using statistical theory and the Wiener–Khinchin theorem. The influence of delay time and light source line width on the power spectrum of dual-frequency coherent signals is analyzed using this formula. The results show that delay time only affects the peak of the power spectrum of the coherent signal. An increase in the line width of the light source broadens the signal power spectrum and reduces the peak value. The necessary condition for distinguishing the Doppler frequency difference is that the theoretical Doppler frequency difference is greater than 1/5 times the line width of the light source.

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18

Borisova, T. D., N. F. Blagoveshchenska, I. V. Moskvin, M. T. Rietveld, M. J. Kosch, and B. Thidé. "Doppler shift simulation of scattered HF signals during the Tromsø HF pumping experiment on 16 February 1996." Annales Geophysicae 20, no. 9 (September 30, 2002): 1479–86. http://dx.doi.org/10.5194/angeo-20-1479-2002.

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Abstract. Comparisons between bistatic scatter measurements and simulation results during the Tromsø HF pumping experiment on 16 February 1996 are made. Doppler measurements of an HF diagnostic signal scattered from the field-aligned irregularities (FAIs) in the auroral E-region were carried out on the London – Tromsø – St. Petersburg path at 9410 kHz from 21:00 to 22:00 UT. The scattered signals were observed both from natural and artificial ionospheric irregularities located in the vicinity of Tromsø. To simulate the Doppler frequency shifts, fd , of scattered signals, a radio channel model, named CONE, was developed. The model allows for ray tracing, group and phase paths, and Doppler frequency shift calculations. The calculated Doppler shifts were analyzed for dependence on the magnitude and direction of plasma velocities in the scattering volume. It was found that the velocity components in the north-south direction are crucial for explaining the Doppler frequency shifts of the scattered diagnostic signals. To simulate fd , real velocities obtained from the EISCAT UHF radar at an altitude of 278 km and from the digital all-sky imager during the experiment were employed. The simulation results of Doppler frequency shift variations with time are in reasonable agreement with the experimental Doppler shifts of scattered signals on the London – Tromsø – St. Petersburg path.Key words. Ionosphere (active experiments; ionospheric irregularities) Radio science (ionospheric propagation)

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19

Thong-un, Natee, and Minoru K. Kurosawa. "Doppler Velocity Estimation of Overlapping Linear-Period-Modulated Ultrasonic Waves Based on an Expectation-Maximization Algorithm." Advances in Acoustics and Vibration 2014 (November 12, 2014): 1–7. http://dx.doi.org/10.1155/2014/921876.

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The occurrence of an overlapping signal is a significant problem in performing multiple objects localization. Doppler velocity is sensitive to the echo shape and is also able to be connected to the physical properties of moving objects, especially for a pulse compression ultrasonic signal. The expectation-maximization (EM) algorithm has the ability to achieve signal separation. Thus, applying the EM algorithm to the overlapping pulse compression signals is of interest. This paper describes a proposed method, based on the EM algorithm, of Doppler velocity estimation for overlapping linear-period-modulated (LPM) ultrasonic signals. Simulations are used to validate the proposed method.

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20

Cao, Xin Liang, Wei Cui, and Meng De Wang. "An Extracting Algorithm of Ultrasonic Doppler Shift for Multiphase Fluid Flow Measurement." Applied Mechanics and Materials 494-495 (February 2014): 817–20. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.817.

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Because of the complexity for the frequency measurement about echo signal of ultrasonic Doppler flow, the acquisition methods directly affect the accuracy of Doppler frequency shift. The algorithm of power spectrum extraction has accurate to detection echo Doppler frequency of stationary signal for the flow-velocity measurement. The key is to obtain relative useful frequency information from complex echo velocity. This study is based on the principle of Doppler velocity measurement, by studying the average frequency algorithm of echoes, and the Fourier transform method is adopted to identify Doppler signal frequency and Doppler frequency shift which was polluted by aliasing noise. The MATLAB simulation results show: the useful frequency to obtain reliable, accurate, and also laid the foundation for the measurement of multiphase flow non-stationary signals.

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21

Yin, Zhao, Jing Jin, Yan Wang, and Yi Shen. "Doppler Signal Denoising Based on Feature Adaptive Wavelet Shrinkage Method." Advanced Materials Research 532-533 (June 2012): 702–7. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.702.

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The envelope extraction of Doppler signal spectrum is very important in ultrasonic blood flow detection, due to the fact that it can provide the diagnosis information of blood circulatory system. Doppler signals are often polluted by noises, which will affect the performance of the envelope extraction. Therefore, it is necessary to remove the noises before extracting the spectrum envelope. In this paper, a Doppler denoising method based on the Feature Adaptive Wavelet Shrinkage is proposed. The advantage of this method is that the threshold of each coefficient is set by using the coefficient at the current location and its two neighbor coefficients. Simulation results demonstrate that the proposed method can remove the noises of Doppler signals more effectively compared to the traditional wavelet threshold method.

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22

Liu, Fang, Chanqing Shen, Qingbo He, Ao Zhang, Fanrang Kong, and Yongbin Liu. "Doppler effect reduction scheme via acceleration-based Dopplerlet transform and resampling method for the wayside acoustic defective bearing detector system." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 18 (April 11, 2014): 3356–73. http://dx.doi.org/10.1177/0954406214530880.

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In a wayside acoustic defective bearing detector system, bearing faults are detected through the analysis of the acoustic signal generated by the bearings of a passing vehicle. As vehicles pass by with high speeds, the acoustic signal recorded by the stationary microphone is disturbed by the Doppler effect. The reduction of the frequential structure disturbance of signals facilitates the efficient diagnosis of bearing faults. This study proposes a Doppler effect reduction scheme for the removal of the frequential structure disturbances of Doppler-shifted signals in the acoustic defective bearing detector system. First, the parameters, including the initial speed and the initial acceleration of the vehicle, are estimated by the acceleration-based Dopplerlet transform via the matching pursuit algorithm. Second, the time vector for resampling is calculated according to the estimated initial speed, the initial acceleration in the first step, the sound speed, and the measured geometric parameters of the ADBD system. Finally, the distorted signal is resampled through spline interpolation. Simulation and experimental cases are used to validate the effectiveness of the proposed scheme. Compared with the steady-motion-based method, the proposed scheme can better capture the true time-varying nature of Doppler-shifted signals. Moreover, this scheme is also robust to noise.

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23

Nam, Jeong-Hun, Jae-Won Rim, Hyunsoo Lee, Il-Seuk Koh, and Jong-Hwa Song. "Modeling of Monopulse Radar Signals Reflected from Ground Clutter in a Time Domain Considering Doppler Effects." Journal of Electromagnetic Engineering and Science 20, no. 3 (July 31, 2020): 190–98. http://dx.doi.org/10.26866/jees.2020.20.3.190.

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To evaluate the performance of a monopulse radar system, it is necessary to accurately model radar return signals from the ground surface in a time domain. In this paper, we propose a numerical method to model these return signals including radar radio frequency specifications, such as the pulse repetition interval, frequency, and polarization, as well as the antenna geometry, the ground clutter backscattering characteristics, and so on. The Doppler effect is also incorporated into the signal generation scheme because of the dynamics of the platform/clutter and the antenna orientation. The Doppler frequency shift caused by the ground clutter is modeled by employing the time correlation of the received signals. In some scenarios, the monopulse signals are generated and numerically examined. For real radar application, the effect of the platform’s roll stabilization on the monopulse signals is investigated based on the proposed signal generation scheme.

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24

Geryes, Maroun, Sebastien Ménigot, Walid Hassan, Ali Mcheick, Jamal Charara, and Jean-Marc Girault. "Detection of Doppler Microembolic Signals Using High Order Statistics." Computational and Mathematical Methods in Medicine 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3243290.

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Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing strokes, which is second cause of mortality worldwide. Transcranial Doppler ultrasound is widely considered the most convenient system for the detection of microemboli. The most common standard detection is achieved through the Doppler energy signal and depends on an empirically set constant threshold. On the other hand, in the past few years, higher order statistics have been an extensive field of research as they represent descriptive statistics that can be used to detect signal outliers. In this study, we propose new types of microembolic detectors based on the windowed calculation of the third moment skewness and fourth moment kurtosis of the energy signal. During energy embolus-free periods the distribution of the energy is not altered and the skewness and kurtosis signals do not exhibit any peak values. In the presence of emboli, the energy distribution is distorted and the skewness and kurtosis signals exhibit peaks, corresponding to the latter emboli. Applied on real signals, the detection of microemboli through the skewness and kurtosis signals outperformed the detection through standard methods. The sensitivities and specificities reached 78% and 91% and 80% and 90% for the skewness and kurtosis detectors, respectively.

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25

LU, Jun, Qunfei ZHANG, Wentao SHI, and Lingling ZHANG. "Doppler estimation and compensation method for underwater target active detection based on communication signal." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 5 (October 2021): 962–70. http://dx.doi.org/10.1051/jnwpu/20213950962.

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The integration of underwater detection and communication uses communication signals to detect a target actively, but the Doppler effect deteriorates the parameter estimation performance of the integrated system. To eliminate the influence of the Doppler effect, a joint Doppler estimation and compensation method based on spectrum zooming and correction is proposed. Firstly, the synchronization signal is used to obtain the signal receiving delay and intercept the single-frequency signal segment in the received signal. Then, the discrete Fourier transform is used to find the frequency that corresponds to the maximum amplitude of the single-frequency signal segment. Finally, the frequency spectrum is refined and corrected within the range near the frequency. The Doppler factor is estimated and the received signal is compensated by the Doppler estimation value. The simulation results show that the proposed method improves Doppler factor estimation accuracy, increases the cross-correlation processing gain and improves DOA (direction of arrival) estimation performance, thus being robust to different Doppler effects.

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26

Leclère, Jérôme, René Landry Jr., and Cyril Botteron. "Comparison of L1 and L5 Bands GNSS Signals Acquisition." Sensors 18, no. 9 (August 23, 2018): 2779. http://dx.doi.org/10.3390/s18092779.

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Nowadays, civil Global Navigation Satellite System (GNSS) signals are available in both L1 and L5 bands. A receiver does not need to acquire independently the signals in both bands coming from a same satellite, since their carrier Doppler and code delay are closely related. Therefore, the question of which one to acquire first rises naturally. Although the common thought would tell the L1 band signals which are narrowband, an accurate comparison has never been done, and the decision is not as easy as it seems. Indeed, L5 band signals have several advantages such as stronger power, lower carrier Doppler, or a pilot channel, unlike the Global Positioning System (GPS) L1 C/A signal. The goal of this paper is therefore to compare the acquisition of L1 and L5 bands signals (GPS L1 C/A and L5, Galileo E1 and E5a/b) to determine which one is more complex and by which factor, in terms of processing time and memory, considering hardware receivers and the parallel code search. The results show that overall the L5 band signals are more complex to acquire, but it depends strongly on the conditions. The E5 signal is always more complex to acquire than E1, while the L5 signal can have a complexity close to the L1 C/A in some cases. Moreover, precise assistance providing accurate Doppler could significantly reduce the L5 complexity below the L1 complexity.

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27

West, B. J., R. Zhang, A. W. Sanders, S. Miniyar, J. H. Zuckerman, and B. D. Levine. "Fractal fluctuations in transcranial Doppler signals." Physical Review E 59, no. 3 (March 1, 1999): 3492–98. http://dx.doi.org/10.1103/physreve.59.3492.

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28

Walsh, James S. "Color Doppler Signals in Breast Diseases." Radiology 192, no. 2 (August 1994): 580. http://dx.doi.org/10.1148/radiology.192.2.580-b.

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29

Brekke, Svein, and Hans Garmann Torp. "Trigger extraction from ultrasound doppler signals." Journal of the Acoustical Society of America 123, no. 2 (2008): 598. http://dx.doi.org/10.1121/1.2857724.

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30

Poepping, Tamie L., Jeremy Gill, Aaron Fenster, and David W. Holdsworth. "MP3 compression of Doppler ultrasound signals." Ultrasound in Medicine & Biology 29, no. 1 (January 2003): 65–76. http://dx.doi.org/10.1016/s0301-5629(02)00696-8.

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31

Warner, M. H., and A. C. Fairhead. "Accurate recording of Doppler ultrasound signals." European Journal of Ultrasound 6 (October 1997): S48. http://dx.doi.org/10.1016/s0929-8266(97)90402-x.

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32

Aineto, M., and S. Lawson. "Detection of zero-Doppler underwater signals." Electronics Letters 34, no. 19 (1998): 1813. http://dx.doi.org/10.1049/el:19981282.

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33

Heringa, A., J. Alsters, J. Hopman, I. van Dam, and O. Daniëls. "Computer processing of cardiac Doppler signals." Medical and Biological Engineering and Computing 26, no. 2 (March 1988): 147–52. http://dx.doi.org/10.1007/bf02442257.

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34

Zhukova, I. N., N. E. Bystrov, and S. D. Chebotarev. "Fast-time and slow-time processing of the pseudorandom amplitude-phase-shift keyed signals." Journal of Physics: Conference Series 2052, no. 1 (November 1, 2021): 012059. http://dx.doi.org/10.1088/1742-6596/2052/1/012059.

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Abstract The two-dimensional raw data structure is used for modern pulse-Doppler radars. Fast-time and slow-time processing of radar return signals is performed. The matched filter compresses each received pulse in fast time. The FFT-based spectral processing of the compressed pulses is then performed in slow time. The two-dimensional structure of raw data has specific features in radars with the transmission and reception of pseudorandom amplitude-phase-shift keyed (APSK) signals to a common aerial. It is formed when the coherent processing interval of the APSK signal is divided into subintervals. The article describes the fast-time and slow-time processing of the APSK signal subintervals. The structure of the signal in the subintervals is also analyzed. The choice of the subinterval duration is discussed. The possible energy losses during the processing of the reflected signals are estimated. The results of the processing modeling of the additive sum of APSK signals with different Doppler frequencies are presented.

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35

Wu, Shi Long, Jing Qing Luo, and Hua Xing Wang. "Single Channel Signal Separation of GMSK Signals Based on MLP." Applied Mechanics and Materials 347-350 (August 2013): 1705–10. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1705.

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In according to the issue of multi-signal jamming in communication reconnaissance, single channel signal separation for multi-GMSK signals has been studied with a method based on MLP. With parameters of Doppler-shift, time-delay, amplitude and coding sequences efficiently estimated, signals could be restructured, and then be separated. Simulations have proved well separation results can be obtained with the method for unequal power signals with certain SNRs.

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36

Semel, M. "Zeeman Doppler Imaging." International Astronomical Union Colloquium 149 (1995): 340–49. http://dx.doi.org/10.1017/s0252921100023290.

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AbstractStellar rotation maps the surface of a star into its line spectrum and gives a dimension to a point on the star - the Doppler dimension. This is of great importance for the detection of Zeeman polarization especially in certain cases. Typically a magnetic configuration will exhibit both polarities, thus the polarization signals of oposite signs may superpose and cancel. The Doppler coordinate will be in general different for parts of the stars having different polarities and therefore the polarization signals will also appear at different wavelengths and will not cancel. Moreover, the time variations plus the Doppler coordinate constitutes two variables that may allow the reconstruction of two dimensional map of the magnetic field over the star surface.Attention will be given to the set-up that allows spectropolarimetry with high spectral resolution and high S/N ratio. The use of cross dispersion spectrographs allows one to observe several tens of spectral lines. The method of adding signals to increase S/N ratio will be indicated.

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37

Qaisar, Sana U., and Craig R. Benson. "Processing Cost of Doppler Search in GNSS Signal Acquisition: Measuring Doppler shift in navigation satellite signals." IEEE Signal Processing Magazine 34, no. 5 (September 2017): 53–58. http://dx.doi.org/10.1109/msp.2017.2715979.

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38

Zeng, Hong-Cheng, Jie Chen, Peng-Bo Wang, Wei Yang, and Wei Liu. "2-D Coherent Integration Processing and Detecting of Aircrafts Using GNSS-Based Passive Radar." Remote Sensing 10, no. 7 (July 23, 2018): 1164. http://dx.doi.org/10.3390/rs10071164.

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Long time coherent integration is a vital method for improving the detection ability of global navigation satellite system (GNSS)-based passive radar, because the GNSS signal is not radar-designed and its power level is very low. For aircraft detection, the large range cell migration (RCM) and Doppler frequency migration (DFM) will seriously affect the coherent processing of azimuth signals, and the traditional range match filter will also be mismatched due to the Doppler-intolerant characteristic of GNSS signals. Accordingly, the energy loss of 2-dimensional (2-D) coherent processing is inevitable in traditional methods. In this paper, a novel 2-D coherent integration processing and algorithm for aircraft target detection is proposed. For azimuth processing, a modified Radon Fourier Transform (RFT) with range-walk removal and Doppler rate estimation is performed. In respect to range compression, a modified matched filter with a shifting Doppler is applied. As a result, the signal will be accurately focused in the range-Doppler domain, and a sufficiently high SNR can be obtained for aircraft detection with a moving target detector. Numerical simulations demonstrate that the range-Doppler parameters of an aircraft target can be obtained, and the position and velocity of the aircraft can be estimated accurately by multiple observation geometries due to abundant GNSS resources. The experimental results also illustrate that the blind Doppler sidelobe is suppressed effectively and the proposed algorithm has a good performance even in the presence of Doppler ambiguity.

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39

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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40

Reddy, D. Karunakar, and T. Satya Savithri. "Area Efficient Rapid Signal Acquisition scheme for High Doppler DSSS Signals." International journal of Computer Networks & Communications 5, no. 2 (March 31, 2013): 71–82. http://dx.doi.org/10.5121/ijcnc.2013.5206.

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41

Abdelazim, Sameh, David Santoro, Mark Arend, Fred Moshary, and Sam Ahmed. "Signal to Noise Ratio Characterization of Coherent Doppler Lidar Backscattered Signals." EPJ Web of Conferences 119 (2016): 17014. http://dx.doi.org/10.1051/epjconf/201611917014.

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42

Yang, Guang, Feng Zhou, Gang Qiao, Yunjiang Zhao, Yufei Liu, Yinheng Lu, and Yuanan He. "Optimized Doppler Estimation and Symbol Synchronization for Mobile M-ary Spread Spectrum Underwater Acoustic Communication." Journal of Marine Science and Engineering 9, no. 9 (September 13, 2021): 1001. http://dx.doi.org/10.3390/jmse9091001.

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In mobile underwater acoustic (UWA) communications, the Doppler effect causes severe signal distortion, which leads to carrier frequency shift and compresses/broadens the signal length. This situation has a more severe impact on communication performance in the case of low signal-to-noise ratio and variable-speed movement. This paper proposes a non-data-aided Doppler estimation method for M-ary spread spectrum UWA communication systems in mobile scenarios. The receiver uses the spread spectrum codes dedicated to transmitting signals with different frequency offsets as local reference signals. Correlation operations are performed symbol by symbol with the received signal. The decoding and Doppler estimation of the present symbol are achieved by searching the correlation maximum in the code domain and frequency domain. The length of the current symbol is corrected for the next symbol synchronization using the estimated Doppler coefficient. To optimize the process of Doppler estimation and symbol synchronization, a heuristic search method is used. By adjusting the Doppler factor search step size, setting the threshold value, and using the Doppler factor estimation of the previous symbol, the search range can be significantly reduced and the computational complexity decreased. The Fisher-Yates shuffle algorithm is used to traverse the search range to ensure reliability of the results. Simulation results show that enlarging the frequency-domain search step size in some degree does not affect the decoding accuracy. On 15 May 2021, a shallow-water mobile UWA spread spectrum communication experiment was conducted in Weihai, China. The horizontal distance between the transmitter and the receiver is 3.7–4.0 km, and the communication rate is 41.96 bits per second. The transmitting ship moves at a speed of 0–3 m/s, and the bit error rate (BER) is lower than 1e−3, which is better than that of the sliding correlation despreading method with average Doppler compensation.

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43

Lan, Xiang, Min Zhang, and Jin-Xing Li. "OFDM Chirp Waveform Design Based on Subchirp Bandwidth Overlap and Segmented Transmitting for Low Correlation Interference in MIMO Radar." Sensors 19, no. 12 (June 14, 2019): 2696. http://dx.doi.org/10.3390/s19122696.

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There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based on chirp signals. The correlation sidelobe peaks level are critical for the detection requirement of MIMO radar signals, however conventional OFDM chirp signals produce high autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP), which reduces detection performance. In this paper, we explore the structure of OFDM chirp signals’ autocorrelation function and proposed a scheme to reduce the designed signal’s ASP by a designing suitable range of subchirp bandwidth and a segmented transmit-receive mode. Next, we explore a suitable range of interval between the chirp rates of each two signals to reduce the CP. The simulation of designed signals verifies the effectiveness of the proposed methods in the reduction of ASP and CP, with the correlation performance being compared with recent relate studies. In addition, the multiple signals detection and one-dimensional range image simulation show the good detection performance of a designed signal in MIMO radar detection.

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44

Tan, Zizhong, Honglei Qin, Li Cong, and Chao Zhao. "Positioning Using IRIDIUM Satellite Signals of Opportunity in Weak Signal Environment." Electronics 9, no. 1 (December 27, 2019): 37. http://dx.doi.org/10.3390/electronics9010037.

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In order to get rid of the dependence of the navigation and positioning system on the global navigation satellite system (GNSS), radio, television, satellite, and other signals of opportunity (SOPs) can be used to achieve receiver positioning. The space-based SOPs based on satellites offer better coverage and availability than ground-based SOPs. Based on the related research of Iridium SOPs positioning in the open environment, this paper mainly focuses on the occluded environment and studies the Iridium SOPs positioning technique in weak signal environment. A new quadratic square accumulating instantaneous Doppler estimation algorithm (QSA-IDE) is proposed after analysing the orbit and signal characteristics of the Iridium satellite. The new method can improve the ability of the Iridium weak signal Doppler estimation. The theoretical analysis and positioning results based on real signal data show that the positioning based on Iridium SOPs can be realized in a weak signal environment. The research broadens the applicable environment of the Iridium SOPs positioning, thereby improving the availability and continuity of its positioning.

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45

Xu, Bing, and Lei Dou. "Novel acquisition of global positioning system signals based on parameter prediction and the chirp z-transform." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 8 (June 6, 2016): 1391–401. http://dx.doi.org/10.1177/0954410016652151.

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The acquisition stage in global positioning system receivers provides a coarse estimation of the Doppler shift and the code phase of the incoming signals. The accuracy of the estimation, especially the Doppler shift, greatly influences the subsequent tracking loops. Based on the parameter prediction and the chirp z-transform algorithm, a novel acquisition approach to acquire the Doppler shift accurately is proposed. The code phase and the Doppler shift are predicted first according to the desired trajectory of the vehicle and satellite ephemeris. Then, frequency refinement of the code-stripped signal is conducted within a small interval around the predicted Doppler shift by using the chirp z-transform algorithm. To reduce the computational load, the data sequence is down-sampled with an integrate and dump accumulator without degrading the performance of the proposed algorithm. Results indicate that, with only 1 ms sampled data, the proposed algorithm can achieve a high-frequency accuracy. Besides, the proposed algorithm can acquire signals with the carrier-to-noise ratio down to 31 dB-Hz.

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46

Shinpaugh, K. A., R. L. Simpson, A. L. Wicks, S. M. Ha, and J. L. Fleming. "Signal-processing techniques for low signal-to-noise ratio laser Doppler velocimetry signals." Experiments in Fluids 12-12, no. 4-5 (March 1992): 319–28. http://dx.doi.org/10.1007/bf00187310.

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47

Farhangian, Farzan, and René Landry. "Multi-Constellation Software-Defined Receiver for Doppler Positioning with LEO Satellites." Sensors 20, no. 20 (October 16, 2020): 5866. http://dx.doi.org/10.3390/s20205866.

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A Multi-Constellation Software-Defined Receiver (MC-SDR) is designed and implemented to extract the Doppler measurements of Low Earth Orbit (LEO) satellite’s downlink signals, such as Orbcomm, Iridium-Next, Globalstar, Starlink, OneWeb, SpaceX, etc. The Doppler positioning methods, as one of the main localization algorithms, need a highly accurate receiver design to track the Doppler as a measurement for Extended Kalman Filter (EKF)-based positioning. In this paper, the designed receiver has been used to acquire and track the Doppler shifts of two different kinds of LEO constellations. The extracted Doppler shifts of one Iridium-Next satellite as a burst-based simplex downlink signal and two Orbcomm satellites as continuous signals are considered. Also, with having the Two-Line Element (TLE) for each satellite, the position, and orbital elements of each satellite are known. Finally, the accuracy of the designed receiver is validated using an EKF-based stationary positioning algorithm with an adaptive measurement matrix. Satellite detection and Doppler tracking results are analyzed for each satellite. The positioning results for a stationary receiver showed an accuracy of about 132 m, which means 72% accuracy advancements compared to single constellation positioning.

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48

Yao, Jiawen, Shan Li, Xiaotong Gu, Yanhao Yin, Geng Chen, and Xiaonan Dai. "A Method for Calculating Dynamic Parameters of Intersatellite Link Signals." Journal of Physics: Conference Series 2093, no. 1 (November 1, 2021): 012028. http://dx.doi.org/10.1088/1742-6596/2093/1/012028.

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Abstract Aiming at the complex dynamic changes of inter-satellite link signals, this paper proposes a low-complexity method to calculate dynamic parameters of inter-satellite link signals so as to simulate inter-satellite link signals with complex dynamic characteristics. Based on the precise ephemeris, the algorithm is used to calculate the transmission delay and Doppler frequency of the signals in an inertial frame of reference by using iteration and interpolation. The calculation result is compared with the result obtained by using the simulation software of the global navigation system. It is found that the error of the transmission delay is at the nanosecond level and the error of Doppler frequency is at the Hertzian level. Therefore, the dynamic signal simulation accuracy can meet the requirements of load testing and verification of inter-satellite links. The algorithm is simple to implement.

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49

Duan, Feng Yang, Li Min Chang, and Ye Zhan. "Realization of the Detecting Method for Aircraft Digital Image Transmission System Based on Multi-Processor." Advanced Materials Research 490-495 (March 2012): 2352–56. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.2352.

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The technologies of image block, pyramid and multi-threading were used in this program to design the high-speed image generation display module and the processes of image data scheduling and mapping and solve the problems of large-capacity image data modeling and high-speed displaying. The technology of direct digital frequency synthesis (DDS) was used to design the Doppler shifting signal generation module and the multi-processor parallel system architecture, which can analog the Doppler frequency shifting of the data communication signals and solve the problem of the authenticity of communication signals during the simulated flight.

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50

Song, Chong, Bingnan Wang, Maosheng Xiang, Zhongbin Wang, Weidi Xu, and Xiaofan Sun. "A Novel Post-Doppler Parametric Adaptive Matched Filter for Airborne Multichannel Radar." Remote Sensing 12, no. 24 (December 8, 2020): 4017. http://dx.doi.org/10.3390/rs12244017.

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The post-Doppler adaptive matched filter (PD-AMF) with constant false alarm rate (CFAR) property was developed for adaptive detection of moving targets, which is a standardized version of the post-Doppler space–time adaptive processing (PD-STAP) in practical applications. However, its detection performance is severely constrained by the training data, especially in a dense signal environment. Improper training data and contamination of moving target signals remarkably degrade the performance of disturbance suppression and result in target cancellation by self-whitening. To address these issues, a novel post-Doppler parametric adaptive matched filter (PD-PAMF) detector is proposed in the range-Doppler domain. Specifically, the detector is introduced via the post-Doppler matched filter (PD-MF) and the lower-diagonal-upper (LDU) decomposition of the disturbance covariance matrix, and the disturbance signals of the spatial sequence are modelled as an auto-regressive (AR) process for filtering. The purpose of detecting ground moving targets as well as for estimating their geographical positions and line-of-sight velocities is achieved when the disturbance is suppressed. The PD-PAMF is able to reach higher performances by using only a smaller training data size. More importantly, it is tolerant to moving target signals contained in the training data. The PD-PAMF also has a lower computational complexity. Numerical results are presented to demonstrate the effectiveness of the proposed detector.

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