Evaluation of the Time Varying Gravity Fields from GRACE Follow-On LRI Instrument

2020 ◽  
Author(s):  
Nadege Pie ◽  
Mark Tamisiea ◽  
Ben Krichman ◽  
Peter Nagel ◽  
Steve Poole ◽  
...  
Keyword(s):  
High Frequency ◽  
Signal To Noise Ratio ◽  
Gravity Models ◽  
Laser Ranging ◽  
Frequency Noise ◽  
Time Varying ◽  
Signal To Noise ◽  
Science Data ◽  
Design Concepts ◽  
Gravity Fields

<p>The Laser Ranging Interferometer (LRI) instrument on-board of the GRACE Follow-On (GRACE-FO) satellites has been collecting science data since a June 2018, a few weeks after launch. Though the LRI instrument, based on design concepts developed for a future LISA mission, was intended mostly as a demonstration instrument, it has far-exceeded its mission requirements and has provided intersatellite ranging observations with improved signal-to-noise ratio compared to the K-Band Ranging (KBR) instrument. The exploitation of the LRI observations has led to a set of monthly gravity field solutions comparable in many ways to the ones obtained from KBR. Though the ranging observations from the LRI have a much lower high-frequency noise content, this has not so far led to an improvement of the time-varying gravity estimates in the spatial domain, while stark differences are visible in the spectral domain between the KBR and LRI fields. We present the series of LRI gravity models in comparison to its KBR counterpart, as well as regional intercomparisons of the gravity solutions against hydrology models.</p>

Research of Terahertz Spectra of Terbutaline Sulfate Based on Wavelet De-Noising

2011 ◽  
Vol 63-64 ◽  
pp. 327-332
Author(s):  
Xiai Chen ◽  
Ping Jie Huang ◽  
Di Bo Hou ◽  
Xu Sheng Kang ◽  
Guang Xin Zhang ◽  
...  
Keyword(s):  
Time Domain ◽  
High Frequency ◽  
Wavelet Decomposition ◽  
Signal To Noise Ratio ◽  
Noise Signal ◽  
Discrete Wavelet ◽  
Frequency Noise ◽  
Signal To Noise ◽  
Terbutaline Sulfate ◽  
Soft Threshold

Terahertz spectra of terbutaline sulfate in the range of 0.2 to 2.2 THz was obtained by THz time-domain spectroscopy. The discrete wavelet transform was applied to de-noising terahertz waveforms. The signal was decomposed into five layers by wavelet decomposition, and then the high-frequency noise signal was eliminated by wavelet reconstruction. Another try was through calculating the standard deviation of the noise signal by the 1-th level signals which got from wavelet decomposition, and then the soft threshold and hard threshold de-noising method was employed respectively. The robustness of these wavelet de-noising methods was testified in this paper, and the absorption and refraction spectra of terbutaline sulfate were got at last. The result of experiment indicts that wavelet can enhance the signal to noise ratio of system and this paper provides a new way for the detection of terbutaline sulfate.

scholarly journals Evaluation of GRACE/GRACE Follow-On Time-Variable Gravity Field Models for Earthquake Detection above Mw8.0s in Spectral Domain

2021 ◽  
Vol 13 (16) ◽  
pp. 3075
Author(s):  
Ming Xu ◽  
Xiaoyun Wan ◽  
Runjing Chen ◽  
Yunlong Wu ◽  
Wenbing Wang
Keyword(s):  
Signal To Noise Ratio ◽  
Time Variable ◽  
Model Errors ◽  
Signal To Noise ◽  
Time Variable Gravity ◽  
Earthquake Detection ◽  
Gravity Fields ◽  
Variable Gravity ◽  
Gravity Recovery ◽  
Gravity Field Models

This study compares the Gravity Recovery And Climate Experiment (GRACE)/GRACE Follow-On (GFO) errors with the coseismic gravity variations generated by earthquakes above Mw8.0s that occurred during April 2002~June 2017 and evaluates the influence of monthly model errors on the coseismic signal detection. The results show that the precision of GFO monthly models is approximately 38% higher than that of the GRACE monthly model and all the detected earthquakes have signal-to-noise ratio (SNR) larger than 1.8. The study concludes that the precision of the time-variable gravity fields should be improved by at least one order in order to detect all the coseismic gravity signals of earthquakes with M ≥ 8.0. By comparing the spectral intensity distribution of the GFO stack errors and the 2019 Mw8.0 Peru earthquake, it is found that the precision of the current GFO monthly model meets the requirement to detect the coseismic signal of the earthquake. However, due to the limited time length of the observations and the interference of the hydrological signal, the coseismic signals are, in practice, difficult to extract currently.

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

Assessment of GRACE-FO Laser Ranging Interferometer measurements

2021 ◽  
Author(s):  
Athina Peidou ◽  
Felix Landerer ◽  
David Wiese ◽  
Matthias Ellmer ◽  
Eugene Fahnestock ◽  
...  
Keyword(s):  
High Frequency ◽  
Signal To Noise Ratio ◽  
Small Scale ◽  
Laser Ranging ◽  
High Signal ◽  
Measurement Sensitivity ◽  
One Year ◽  
Mass Transfers ◽  
Gravity Recovery ◽  
System Errors

<p>The performance of Gravity Recovery and Climate Experiment Follow‐On (GRACE-FO) laser ranging interferometer (LRI) system is assessed in both space and frequency domains. With LRI’s measurement sensitivity being as small as 0.05 nm/s<sup>2</sup> at GRACE-FO altitude we perform a thorough assessment on the ability of the instrument to detect real small-scale high-frequency gravity signals. Analysis of range acceleration measurements along the orbit for nearly one year of daily solutions suggests that LRI can detect signals induced by mass perturbation up to 26 mHz, i.e., ~145 km spatial resolution. Additionally, high frequency signals that are not adequately modeled by dealiasing models are clearly detected and their magnitude is shown to reach 2-3 nm/s<sup>2</sup>. The alternative K‐band microwave ranging system (KBR) is also examined and results demonstrate the inability of KBR to retrieve signals above 15mHz (i.e., shorter than ~200 km) as the noise of the KBR range acceleration increases rapidly. Overall, the first stream of LRI measurements shows that the high signal to noise ratio allows for detection of mass transfers in finer scales, however the ability to fully exploit the high-quality signal measured by the LRI in Level 2 products is still constrained by noise of background models and other onboard instrumentation and measurement system errors.</p><p>Copyright Acknowledgment: This work was performed at the California Institute of Technology's Jet Propulsion Laboratory under a contract with the National Aeronautics and Space Administration's Cryosphere Science Program.</p>

Multichannel absorption compensation with a data-driven structural regularization

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. V71-V80 ◽  
Author(s):  
Xiong Ma ◽  
Guofa Li ◽  
Hao Li ◽  
Wuyang Yang
Keyword(s):  
Cost Function ◽  
Structural Characteristic ◽  
Seismic Data ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Frequency Noise ◽  
Characteristic Operator ◽  
High Frequency Noise ◽  
The Cost

Seismic absorption compensation is an important processing approach to mitigate the attenuation effects caused by the intrinsic inelasticity of subsurface media and to enhance seismic resolution. However, conventional absorption compensation approaches ignore the spatial connection along seismic traces, which makes the compensation result vulnerable to high-frequency noise amplification, thus reducing the signal-to-noise ratio (S/N) of the result. To alleviate this issue, we have developed a structurally constrained multichannel absorption compensation (SC-MAC) algorithm. In the cost function of this algorithm, we exploit an [Formula: see text] norm to constrain the reflectivity series and an [Formula: see text] norm to regularize the reflection structural characteristic of the compensation data. The reflection structural characteristic operator, extracted from the observed stacked seismic data, is the core of the structural regularization term. We then solve the cost function of SC-MAC by the alternating direction method of multipliers. Benefiting from the introduction of reflection structure constraint, SC-MAC improves the stability of the compensation result and inhibits the amplification of high-frequency noise. Synthetic and field data examples demonstrate that our proposed method is more robust to random noise and can not only improve the resolution of seismic data, but also maintain the S/N of the compensation seismic data.

Coding of time-varying electric field amplitude modulations in a wave-type electric fish

1996 ◽  
Vol 75 (6) ◽  
pp. 2280-2293 ◽  
Author(s):  
R. Wessel ◽  
C. Koch ◽  
F. Gabbiani
Keyword(s):  
Mutual Information ◽  
Electric Fish ◽  
Signal To Noise Ratio ◽  
Cutoff Frequency ◽  
Spike Trains ◽  
Time Varying ◽  
Signal To Noise ◽  
Single Spike ◽  
The Mean ◽  
P Type

1. The coding of time-varying electric fields in the weakly electric fish, Eigenmannia, was investigated in a quantitative manner. The activity of single P-type electroreceptor afferents was recorded while the amplitude of an externally applied sinusoidal electric field was stochastically modulated. The amplitude modulation waveform (i.e., the stimulus) was reconstructed from the spike trains by mean square estimation. 2. From the stimulus and the reconstructions we calculated the following: 1) the signal-to-noise ratio and thus an effective temporal bandwidth of the units; 2) the coding fraction, i.e., a measure of the fraction of the time-varying stimulus encoded in single spike trains; and 3) the mutual information provided by the reconstructions about the stimulus. 3. Signal-to-noise ratios as high as 7:1 were observed and the bandwidth ranged from 0 up to 200 Hz, consistent with the limit imposed by the sampling theorem. Reducing the cutoff frequency of the stimulus increased the signal-to-noise ratio at low frequencies, indicating a nonlinearity in the receptors' response. 4. The coding fraction and the rate of mutual information transmission increased in parallel with the standard deviation (i.e., the contrast) of the stimulus as well as the mean firing rate of the units. Significant encoding occurred 20-40 Hz above the spontaneous discharge of a unit. 5. When the temporal cutoff frequency of the stimulus was increased between 80 and 400 Hz, 1) the coding fraction decreased, 2) the rate of mutual information transmission remained constant over the same frequency range, and 3) the reconstructed filter changed. This is in agreement with predictions obtained in a simplified neuronal model. 6. Our results suggest that 1) the information transmitted by single spike trains of primary electrosensory afferents to higherorder neurons in the fish brain depends on the contrast and the cutoff frequency of the stimulus as well as on the mean firing rate of the units; and 2) under optimal conditions, more than half of the information about a Gaussian stimulus that can in principle be encoded is carried in single spike trains of P-type afferents at rates up to 200 bits per second.

scholarly journals 53 Piscium, an SPB Star with Activity

2002 ◽  
Vol 185 ◽  
pp. 236-237
Author(s):  
J.-M. Le Contel ◽  
P. Mathias ◽  
E. Chapellier ◽  
J.-C. Valtier
Keyword(s):  
High Resolution ◽  
False Alarm ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Correlation Technique ◽  
Signal To Noise ◽  
Spectroscopic Observations ◽  
Auto Correlation ◽  
Frequency Variations

The star 53 Psc (HD 3379, B2.5IV) has been observed as variable by several authors (Sareyan et al., 1979) with frequencies around 10 c d–1 and has been classified as a β Cephei star. Conversely, other authors (e.g. Percy, 1971) found it to be constant.New high resolution, high signal-to-noise ratio, Spectroscopic observations have been performed at the Observatoire de Haute-Provence in 1996 over 11 nights. The spectral domain covers around 200 Å and is centered on Hδ. Radial velocities were deduced from an auto-correlation technique with a scatter around 0.4kms−1.No high frequency variations are observed. Three frequencies have been detected with a false alarm detection above the 1 % level. A fourth one may be present but its amplitude is below this 1 % level. Results are displayed in Table 1.

Detecting and Predicting Early Faults of Complex Rotating Machinery Based on Cyclostationary Time Series Model

2006 ◽  
Vol 128 (5) ◽  
pp. 666-671 ◽  
Author(s):  
Z. S. Chen ◽  
Y. M. Yang ◽  
Z. Hu ◽  
G. J. Shen
Keyword(s):  
Signal To Noise Ratio ◽  
Rotating Machinery ◽  
Ar Model ◽  
Model Parameters ◽  
Time Varying ◽  
Signal To Noise ◽  
Vibration Signals ◽  
Novel Method ◽  
Cyclostationary Signals ◽  
Gear Crack

Vibration signals of complex rotating machinery are often cyclostationary, so in this paper one novel method is proposed to detect and predict early faults based on the linear (almost) periodically time-varying autoregressive (LPTV-AR) model. At first the algorithms of identifying model parameters and order are presented using the higher-order cyclic-cumulant, which can suppress additive stationary noises and improve the signal to noise ratio (SNR). Then numerical simulations are done and the results indicate that this model is more effective for cyclostationary signals than the classical AR model. In the end the proposed method is used for detecting incipient gear crack fault in a helicopter gearbox. The results demonstrate that the approach can be used to detect and predict early faults of complex rotating machinery by the kurtosis of the residual signal.

Threshold Noise Reduction Research of Improved EEMD Method

2012 ◽  
Vol 226-228 ◽  
pp. 237-240 ◽  
Author(s):  
Mei Jun Zhang ◽  
Hao Chen ◽  
Chuang Wang ◽  
Qing Cao
Keyword(s):  
Noise Reduction ◽  
Signal To Noise Ratio ◽  
Frequency Noise ◽  
Signal To Noise ◽  
Time Frequency ◽  
Noise Ratio ◽  
Reduction Effect ◽  
Eemd Method ◽  
Simulation Signal ◽  
Improved Eemd

In order to extract effectively detection signals in the noise background for non-stationary signal.On the basis of EEMD, improved EEMD is put forward, the improve EEMD threshold noise reduction is researched in this paper.The simulation signal compared the noise reduction effect of the wavelet,EMD,EEMD,and the improved EEMD. The improved EEMD threshold noise reduction have the best noise reduction result , the highest signal-to-noise ratio, the smallest standard deviation error.After the improved EEMD threshold noise reduction , the measurement signal time domain waveform smooth. More high frequency noise was obviously reduced in Hilbert time- frequency spectrum. Signal-to-noise ratio significantly improve, and signal characteristics are very clear.

scholarly journals Effects of Noise and Absorption on High Frequency Measurements of Acoustic-Backscatter from Fish

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Masahiko Furusawa
Keyword(s):  
Measurement Error ◽  
Environmental Conditions ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Target Strength ◽  
Acoustic Backscatter ◽  
Signal To Noise ◽  
Absorption Coefficients ◽  
Frequency Measurements ◽  
Multiple Frequencies

Quantitative echosounders operating at multiple frequencies (e.g., 18, 38, 70, 120, 200, 333, and 710 kHz) are often used to observe fish and zooplankton and identify their species. At frequencies above 100 kHz, the absorption attenuation increases rapidly and decreases the signal-to-noise ratio (SNR). Also, incomplete compensation for the attenuation may result in measurement error. This paper addresses the effects of the attenuation and noise on high frequency measurements of acoustic backscatter from fish. It is shown that measurements of a fish with target strength of −40 dB at 200 m depth are limited by SNR to frequencies up to about 100 kHz. Above 100 kHz, absorption coefficients must be matched to local environmental conditions.

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