Methods for the robust computation of the long-period seismic spectrum of broad-band arrays

2020 ◽  
Vol 222 (3) ◽  
pp. 1480-1501
Author(s):  
Ross C Caton ◽  
Gary L Pavlis ◽  
David J Thomson ◽  
Frank L Vernon
Keyword(s):  
Signal To Noise Ratio ◽  
Spectral Band ◽  
Broad Band ◽  
Low Noise ◽  
Small Aperture ◽  
Transient Signals ◽  
Seismic Arrays ◽  
Low Snr ◽  
Long Period ◽  
Student’S T

SUMMARY We describe array methods to search for low signal-to-noise ratio (SNR) signals in long-period seismic data using Fourier analysis. This is motivated by published results that find evidence of solar free oscillations in the Earth's seismic hum. Previous work used data from only one station. In this paper, we describe methods for computing spectra from array data. Arrays reduce noise level through averaging and provide redundancy that we use to distinguish coherent signal from a random background. We describe two algorithms for calculating a robust spectrum from seismic arrays, an algorithm that automatically removes impulsive transient signals from data, a jackknife method for estimating the variance of the spectrum, and a method for assessing the significance of an entire spectral band. We show examples of their application to data recorded by the Homestake Mine 3-D array in Lead, SD and the Piñon Flats PY array. These are two of the quietest small aperture arrays ever deployed in North America. The underground Homestake data has exceptionally low noise, and the borehole sensors of the PY array also have very low noise, making these arrays well suited to finding very weak signals. We find that our methods remove transient signals effectively from the data so that even low-SNR signals in the seismic background can be found and tested. Additionally, we find that the jackknife variance estimate is comparable to the noise floor, and we present initial evidence for solar g-modes in our data through the T2 test, a multivariate generalization of Student's t-test.

The seismic broad-band antenna of the Low Noise Underground Laboratory (LSBB, Rustrel, France): a tool for measuring the rotation ground motion.

2020 ◽  
Author(s):  
Olivier Sèbe ◽  
Stéphane Gaffet ◽  
Roxanne Rusch ◽  
Jean-Baptiste Decitre ◽  
Charly Lallemand ◽  
...  
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Broad Band ◽  
Low Noise ◽  
Underground Laboratory ◽  
Finite Difference Approximation ◽  
Difference Approximation ◽  
Spatial Gradient ◽  
Small Aperture ◽  
Seismic Wavefield

<p>I<span>n the last 20 years, seismologists have recognized that a better sensing of the seismic wavefield is obtained by considering the rotational ground motions in addition to the translation measurements usually provided by seismometers. Even though recent technological developments have resulted in new portable rotation sensors with a sensitivity and a bandwidth suited to seismological applications requirements, the ground rotations have for a long time been estimated indirectly by dense seismic arrays.</span></p><p><span>The Low Noise Underground Laboratory (LSBB) includes a dense 3D seismic antenna composed of 6 STS2 broad-band seismometers since March 2005. From 2016, this array has been upgraded by the installation of about 10 new seismometers at the surface and inside the galleries of the laboratory. Thanks to these dense and small aperture seismic networks, the vertical and horizontal rotations of the ground motion have been estimated by finite difference approximation of the spatial derivatives of the local ground motions. These measurements provide the opportunity to conduct six degree of freedom (6DOF) analysis (3C translations and 3C rotations) to find out the direction of the wave propagation and to estimate the seismic wave local phase velocity. </span></p><p><span>The performance of this seismic array in deriving the local spatial gradient of the seismic wavefield, as well as the rotation tensor, will be illustrated by several selected seismic records such as the 2016 central Italy crisis (Amatrice and Norcia events) as well as the recent local Teil earthquake. In addition, the Array Derived Rotations (ADR) from the LSBB antenna are compared with the rotations measured by different kinds of rotation sensors including 2 prototypes of the new BlueSeis3A and a Lily Borehole Tiltmeter.</span></p>

scholarly journals Radar Signals Modulation Recognition Based on Bispectrum Feature Processing

2021 ◽  
Author(s):  
xinping mi ◽  
xihong Chen ◽  
yufei Cao ◽  
qiang liu ◽  
xincheng song
Keyword(s):  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Low Noise ◽  
Modulation Recognition ◽  
Algorithm Optimization ◽  
Noise Resistance ◽  
Suppression Effect ◽  
Low Snr ◽  
Bee Colony ◽  
Radar Signals

Abstract Modulation recognition of radar signals is an important part of modern electronic intelligence reconnaissance and electronic support systems. In this paper, to solve the problem of low recognition accuracy and low noise resistance of radar signals under low signal-to-noise ratio(SNR), a recognition method based on variational mode decomposition(VMD) and bispectrum feature extraction is proposed. Based on the feature that bispectrum can suppress Gaussian noise, the feasibility of signals modulation recognition under low SNR is analyzed and the noise item is introduced. Due to the interference of noise item, the noise suppression effect of bispectrum is worse under 0dB. An improved VMD algorithm based on artificial bee colony(ABC) algorithm optimization and envelope entropy evaluation is proposed to preprocess the signal to improve the SNR. Finally, we designed a convolution neural network(CNN) classifier to recognize signals of different modulation types. The simulation results show that this method has better noise resistance than traditional methods, and can effectively identify different types of signals under low SNR.

Modal frequencies of bridges from GNSS (GPS) monitoring data: Experimental, statistical evidence

2021 ◽  
Vol 17 (1-2) ◽  
pp. 3-14
Author(s):  
Stathis C. Stiros ◽  
F. Moschas ◽  
P. Triantafyllidis
Keyword(s):  
Signal To Noise Ratio ◽  
Vertical Axis ◽  
Bridge Monitoring ◽  
Low Snr ◽  
True Value ◽  
Gps Satellites ◽  
Wide Range ◽  
Spectral Peaks ◽  
Monitoring Survey ◽  
True Frequency

GNSS technology (known especially for GPS satellites) for measurement of deflections has proved very efficient and useful in bridge structural monitoring, even for short stiff bridges, especially after the advent of 100 Hz GNSS sensors. Mode computation from dynamic deflections has been proposed as one of the applications of this technology. Apart from formal modal analyses with GNSS input, and from spectral analysis of controlled free attenuating oscillations, it has been argued that simple spectra of deflections can define more than one modal frequencies. To test this scenario, we analyzed 21 controlled excitation events from a certain bridge monitoring survey, focusing on lateral and vertical deflections, recorded both by GNSS and an accelerometer. These events contain a transient and a following oscillation, and they are preceded and followed by intervals of quiescence and ambient vibrations. Spectra for each event, for the lateral and the vertical axis of the bridge, and for and each instrument (GNSS, accelerometer) were computed, normalized to their maximum value, and printed one over the other, in order to produce a single composite spectrum for each of the four sets. In these four sets, there was also marked the true value of modal frequency, derived from free attenuating oscillations. It was found that for high SNR (signal-to-noise ratio) deflections, spectral peaks in both acceleration and displacement spectra differ by up to 0.3 Hz from the true value. For low SNR, defections spectra do not match the true frequency, but acceleration spectra provide a low-precision estimate of the true frequency. This is because various excitation effects (traffic, wind etc.) contribute with numerous peaks in a wide range of frequencies. Reliable estimates of modal frequencies can hence be derived from deflections spectra only if excitation frequencies (mostly traffic and wind) can be filtered along with most measurement noise, on the basis of additional data.

scholarly journals Convolution Network with Custom Loss Function for the Denoising of Low SNR Raman Spectra

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4623
Author(s):  
Sinead Barton ◽  
Salaheddin Alakkari ◽  
Kevin O’Dwyer ◽  
Tomas Ward ◽  
Bryan Hennelly
Keyword(s):  
Raman Spectra ◽  
Loss Function ◽  
Signal To Noise Ratio ◽  
Biomedical Science ◽  
Clinical Tool ◽  
Signal To Noise ◽  
Low Snr ◽  
Low Intensity ◽  
Spectral Peaks ◽  
Noise Ratio

Raman spectroscopy is a powerful diagnostic tool in biomedical science, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra. A key component in the classification of Raman spectra is the application of multi-variate statistical models. However, Raman scattering is a weak process, resulting in a trade-off between acquisition times and signal-to-noise ratios, which has limited its more widespread adoption as a clinical tool. Typically denoising is applied to the Raman spectrum from a biological sample to improve the signal-to-noise ratio before application of statistical modeling. A popular method for performing this is Savitsky–Golay filtering. Such an algorithm is difficult to tailor so that it can strike a balance between denoising and excessive smoothing of spectral peaks, the characteristics of which are critically important for classification purposes. In this paper, we demonstrate how Convolutional Neural Networks may be enhanced with a non-standard loss function in order to improve the overall signal-to-noise ratio of spectra while limiting corruption of the spectral peaks. Simulated Raman spectra and experimental data are used to train and evaluate the performance of the algorithm in terms of the signal to noise ratio and peak fidelity. The proposed method is demonstrated to effectively smooth noise while preserving spectral features in low intensity spectra which is advantageous when compared with Savitzky–Golay filtering. For low intensity spectra the proposed algorithm was shown to improve the signal to noise ratios by up to 100% in terms of both local and overall signal to noise ratios, indicating that this method would be most suitable for low light or high throughput applications.

scholarly journals Estimation of singly transiting K2 planet periods with Gaia parallaxes

2019 ◽  
Vol 489 (3) ◽  
pp. 3149-3161 ◽  
Author(s):  
Emily Sandford ◽  
Néstor Espinoza ◽  
Rafael Brahm ◽  
Andrés Jordán
Keyword(s):  
Direct Measurement ◽  
Free Parameter ◽  
Broad Band ◽  
Long Period ◽  
Period Distribution ◽  
Typical Period ◽  
Stellar Models ◽  
Host Stars ◽  
Stellar Density ◽  
As If

ABSTRACT When a planet is only observed to transit once, direct measurement of its period is impossible. It is possible, however, to constrain the periods of single transiters, and this is desirable as they are likely to represent the cold and far extremes of the planet population observed by any particular survey. Improving the accuracy with which the period of single transiters can be constrained is therefore critical to enhance the long-period planet yield of surveys. Here, we combine Gaia parallaxes with stellar models and broad-band photometry to estimate the stellar densities of K2 planet host stars, then use that stellar density information to model individual planet transits and infer the posterior period distribution. We show that the densities we infer are reliable by comparing with densities derived through asteroseismology, and apply our method to 27 validation planets of known (directly measured) period, treating each transit as if it were the only one, as well as to 12 true single transiters. When we treat eccentricity as a free parameter, we achieve a fractional period uncertainty over the true single transits of $94^{+87}_{-58}{{\ \rm per\ cent}}$, and when we fix e = 0, we achieve fractional period uncertainty $15^{+30}_{-6}{{\ \rm per\ cent}}$, a roughly threefold improvement over typical period uncertainties of previous studies.

Broad-band EDFA gain flattening by using an embedded long-period fiber grating filter

2007 ◽  
Vol 271 (2) ◽  
pp. 377-381 ◽  
Author(s):  
N. Ni ◽  
C.C. Chan ◽  
K.M. Tan ◽  
S.C. Tjin ◽  
X.Y. Dong
Keyword(s):  
Broad Band ◽  
Fiber Grating ◽  
Long Period Fiber Grating ◽  
Long Period ◽  
Gain Flattening ◽  
Period Fiber Grating

scholarly journals Automotive antenna diversity system for satellite radio with high phase accuracy in low SNR-scenarios

2018 ◽  
Vol 10 (5-6) ◽  
pp. 578-586 ◽  
Author(s):  
Simon Senega ◽  
Ali Nassar ◽  
Stefan Lindenmeier
Keyword(s):  
Signal To Noise Ratio ◽  
A Priori ◽  
Multipath Fading ◽  
Correction Method ◽  
Antenna System ◽  
Antenna Diversity ◽  
Phase Detection ◽  
Low Snr ◽  
Single Antenna ◽  
Noise Correction

AbstractFor a fast scan-phase satellite radio antenna diversity system a noise correction method is presented for a significant improvement of audio availability at low signal-to-noise ratio (SNR) conditions. An error analysis of the level and phase detection within the diversity system in the presence of noise leads to a correction method based on a priori knowledge of the system's noise floor. This method is described and applied in a hardware example of a satellite digital audio radio services antenna diversity circuit for fast fading conditions. Test drives, which have been performed in real fading scenarios, are described and results are analyzed statistically. Simulations of the scan-phase antenna diversity system show higher signal amplitudes and availabilities. Measurement results of dislocated antennas as well as of a diversity antenna set on a single mounting position are presented. A comparison of a diversity system with noise correction, the same system without noise correction, and a single antenna system with each other is performed. Using this new method in fast multipath fading driving scenarios underneath dense foliage with a low SNR of the antenna signals, a reduction in audio mute time by one order of magnitude compared with single antenna systems is achieved with the diversity system.

Gravity meter observation of free modes excited by the August 19, 1977 Indonesia earthquake

1979 ◽  
Vol 69 (5) ◽  
pp. 1445-1454
Author(s):  
John A. Linton ◽  
D. E. Smylie ◽  
O. G. Jensen
Keyword(s):  
Signal To Noise Ratio ◽  
Quartz Fiber ◽  
Large Signal ◽  
Signal To Noise ◽  
Definitive Evidence ◽  
Long Period ◽  
Noise Ratio

abstract Free modes with signal-to-noise ratio in the range of 40 to 55 dB were observed in the record taken by a vertical broadband quartz fiber gravimeter system opeating in Montreal following the event of August 19, 1977 in Indonesia. The large signal-to-noise ratio has permitted very stable Q estimates to be made for a number of the fundamental spheroidal modes. The very long-period band shows no definitive evidence of signal other than the expected tidal lines.

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