On the Detectability of Synthetic Disturbances in FG5 Absolute Gravimetry Data Using Lomb-Scargle Analysis

GEOMATICA ◽  
2012 ◽  
Vol 66 (2) ◽  
pp. 113-124 ◽  
Author(s):  
Martin Orlob ◽  
Alexander Braun
Keyword(s):  
Spectral Analysis ◽  
Signal To Noise Ratio ◽  
Sensitivity Function ◽  
Adjustment Process ◽  
Environmental Disturbance ◽  
Signal To Noise ◽  
Absolute Gravimetry ◽  
Disturbance Parameter ◽  
Periodogram Analysis ◽  
Frequency Phase

An instrumental or environmental disturbance (signal plus noise) in FG5 absolute gravimetry observations becomes visible by analyzing the residuals, which represent the misfit from the theoretical acceleration parabola. While spectral analysis of FG5 residuals via classical discrete Fourier transform (DFT) is limited by the non-equispaced nature of the FG5 observations, the Lomb-Scargle periodogram can analyze nonequispaced observations and estimate (detect) signals in FG5 residuals. We investigate the detectability of synthetically introduced disturbances in FG5 residuals using Lomb-Scargle periodogram analysis. The sensitivity of the FG5 measurement and adjustment process is a function of disturbance frequency, amplitude, phase, and signal-to-noise ratio (SNR). We conclude that the used drop length and the transfer function of the instrument can significantly alter the estimated gravity values. Further, we establish a sensitivity function called LOFSMAP which depends on the disturbance parameter space of amplitude, frequency, phase and SNR.

Resolving phase wrapping by using sliding transform for generation of dispersion curves

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. V127-V136 ◽  
Author(s):  
Jyant Kumar ◽  
Tarun Naskar
Keyword(s):  
Spectral Analysis ◽  
Surface Wave ◽  
Surface Waves ◽  
Test Data ◽  
Signal To Noise Ratio ◽  
Phase Unwrapping ◽  
Signal To Noise ◽  
Manual Intervention ◽  
Multichannel Analysis ◽  
Synthetic Test

The complexity involved with the phase unwrapping procedure, while performing the existing spectral analysis of surface waves (SASW) on the basis of two sensors, makes it difficult to automate and requires frequent manual judgment. As a result, this approach generally becomes tedious and may yield erroneous results. The multichannel analysis of surface waves (MASW) technique can resolve the problem of phase wrapping. However, the MASW technique normally requires a large number of closely spaced sensors, typically 24–48 or even more. We have developed a new method that is fast, accurate, and generally resolves the unwrapping of phase with the use of just two sensors, provided the signal-to-noise ratio remains high. In this approach, the unwrapping of the phase can be performed without any manual intervention and an automation of the process becomes feasible. A few examples, involving synthetic test data and surface-wave tests, have been tested to determine the efficacy of our approach. Comparisons of the results have been made with the corresponding solutions using existing SASW and MASW techniques.

Bearing Fault Detection Using Adaptive Noise Cancelling

1982 ◽  
Vol 104 (2) ◽  
pp. 280-289 ◽  
Author(s):  
G. K. Chaturvedi ◽  
D. W. Thomas
Keyword(s):  
Spectral Analysis ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Primary Input ◽  
Analysis Techniques ◽  
Noise Cancelling ◽  
Adaptive Noise ◽  
Correlated Signals ◽  
Correlated Noises ◽  
Reference Input

The ability to diagnose a mechanical fault is enhanced if the monitoring signal can be preprocessed to reduce the effect of unwanted noise. To this end, the adaptive noise cancelling technique (ANC) can substantially improve the signal to noise ratio where the required signal is contaminated by noise. ANC makes use of two inputs—a primary input which contains the corrupted signal, and a reference input containing noise correlated in some unknown way with the primary noise. A variation of ANC is also proposed and it is shown that this can be applied effectively in those situations where inputs contain correlated signals but uncorrelated or weakly correlated noises. Using vibrational data derived from a reasonably complex bearing rig and preprocessing the data by the ANC technique, this paper shows that the statistical and spectral analysis techniques can be made more effective in their diagnostic roles after the application of ANC.

scholarly journals Multitaper spectral analysis of atmospheric radar signals

2004 ◽  
Vol 22 (11) ◽  
pp. 3995-4003 ◽  
Author(s):  
V. K. Anandan ◽  
C. J. Pan ◽  
T. Rajalakshmi ◽  
G. Ramachandra Reddy
Keyword(s):  
Spectral Analysis ◽  
Lower Stratosphere ◽  
Signal To Noise Ratio ◽  
Power Spectra ◽  
Estimation Accuracy ◽  
Doppler Width ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Width Measurements ◽  
Backscattered Signals

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.

scholarly journals Asymptotic Performances of a Signal-To-Noise Ratio Moment-Based Estimator for Real Sinusoids in Additive Noise

2019 ◽  
Vol 9 (24) ◽  
pp. 5556 ◽  
Author(s):  
Gianmarco Romano
Keyword(s):  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Noise Power ◽  
Signal To Noise ◽  
Practical Applications ◽  
Unknown Variance ◽  
Noise Ratio ◽  
Asymptotic Variances ◽  
Frequency Phase ◽  
General Method

We considered the problem of the estimation of signal-to-noise ratio (SNR) with a real deterministic sinusoid with unknown frequency, phase and amplitude in additive Gaussian noise of unknown variance. A blind SNR estimator that does not require the knowledge of the instantaneous frequency of the sinusoid, through separate estimation of signal and noise power, was derived using the method of moments, a general method to derive estimators based on high-order moments. Statistical performances of the proposed estimators were studied theoretically through derivation of Cramer–Rao lower bounds (CRLBs) and asymptotic variances. Furthermore, results from Monte-Carlo simulations that confirm the validity of the theoretical analysis are presented along with some comments on the use of proposed estimators in practical applications.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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