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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Criteria and algorithms for spectrum parameterization of MST radar signals

The power spectra S(f) of MST radar signals contain useful information about the variance of refractivity fluctuations, the mean radial velocity, and the radial velocity variance in the atmosphere. When noise and other contaminating signals are absent, these quantities can be obtained directly from the zeroth, first and second order moments of the spectra. A step-by-step procedure is outlined that can be used effectively to reduce large amounts of MST radar data-averaged periodograms measured in range and time to a parameterized form. The parameters to which a periodogram can be reduced are outlined and the steps in the procedure, that may be followed selectively, to arrive at the final set of reduced parameters are given. Examples of the performance of the procedure are given and its use with other radars are commented on.

Rastogi, P. K.↗
NASA NTRS1998

Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition

Taguchi Methods of Robust Design presents a way to optimize output process performance through an organized set of experiments by using orthogonal arrays. Analysis of variance and signal-to-noise ratio is used to evaluate the contribution of each of the process controllable parameters in the realization of the process optimization. In the photoresist deposition process, there are numerous controllable parameters that can affect the surface quality and thickness of the final photoresist layer.

Taguchi Method Shipley SJR 5740 orthogonal arrays ↗
NASA NTRS2005

The development of a Kalman filter clock predictor

A Kalman filter based clock predictor is developed, and its performance evaluated using both simulated and real data. The clock predictor is shown to possess a neat to optimal Prediction Error Variance (PEV) when the underlying noise consists of one of the power law noise processes commonly encountered in time and frequency measurements. The predictor's performance is the presence of multiple noise processes is also examined. The relationship between the PEV obtained in the presence of multiple noise processes and those obtained for the individual component noise processes is examined. Comparisons are made with a simple linear clock predictor. The clock predictor is used to predict future values of the time offset between pairs of NPL's active hydrogen masers.

clock predictor↗
NASA NTRS1978

Signal detection in l/f noise of SQUID magnetometers

It is shown that the variance on the SQUID power spectrum in the l/f low frequency region is well behaved, i.e., any small frequency band may be treated as white noise in standard power spectrum estimation theory. Specifically a calibration signal is examined at 0.017 Hz with an equivalent energy referred to the SQUID input coil of 1 times 10 to the -30th J and a digitally recorded and analyzed record of 140 hr duration obtained an optimum S/N better than 400. The results are in good agreement with theory. In addition no deviation from the l/f dependence of the noise energy spectrum is seen down to frequencies below 10 to the -5th Hz. A commercially available SQUID and electronics system were used.

Cabrera, B.↗
NASA NTRS1977

DSN system performance test Doppler noise models; noncoherent configuration

The newer model for variance, the Allan technique, now adopted for testing, is analyzed in the subject mode. A model is generated (including considerable contribution from the station secondary frequency standard), and rationalized with existing data. The variance model is definitely sound; the Allan technique mates theory and measure. The mean-frequency model is an estimate; this problem is yet to be rigorously resolved. The unaltered defining expressions are noncovergent, and the observed mean is quite erratic.

Bunce, R.↗
NASA NTRS1988

A variance based confidence criterion for ERA identified modal parameters

The realization theory is developed in a systematic manner for the Eigensystem Realization Algorithm (ERA) used for system identification. First, perturbation results are obtained which describe the linearized changes in the identified parameters resulting from small change in the data. Formulas are then derived that can be used to evaluate the variance of each of the identified parameters, assuming that the noise level is sufficiently low to allow the application of linearized results. These variances can be converted to give confidence intervals for each of the parameters for any chosen confidence level.

Longman, Richard W.↗
NASA NTRS2004

Mesoscale Gravity Wave Variances from AMSU-A Radiances

A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.

middle atmosphere↗
NASA NTRS1973

Maximum likelihood synchronizer for binary overlapping PCM/NRZ signals.

A maximum likelihood parameter estimation technique for the self bit synchronization problem is investigated. The input sequence to the bit synchronizer is a sequence of binary overlapping PCM/NRZ signal in the presence of white Gaussian noise with zero mean and known variance. The resulting synchronizer consists of matched filters, a transition device and a weighting function. Finally, the performance is examined by Monte Carlo simulations.

Wang, C. D.↗
NASA NTRS2018

ATMS Radiometric Noise Characterization

The Advanced Technology Microwave Sounder (ATMS), on SNPP and NOAA-20, provides vertical atmospheric temperature and moisture profiles that are a key input to numerical weather prediction. Full characterization of radiometric noise is critical to error modeling, algorithm development and the potential development of performance requirements and product improvements. This paper presents estimates of white noise and low-frequency 1/f noise as derived from the Allan variance and scan-to-scan autocorrelations of data from the internal hot calibration. This approach allows direct comparison of on-orbit performance of the two units as well as comparison between ground calibration test data and on-orbit performance. The autocorrelation at multiple scan intervals is used as input to a theoretical model of the NET of inferred scene brightness temperature, when using weighted samples of calibration data over multiple scans. This will support selection of optimized calibration weighting functions for each channel, as well as providing further insight into the striping phenomenon. These measured autocorrelations are also compared to the autocorrelations derived from the 1/f spectra obtained both in special ground and on-orbit tests that characterize gain fluctuation. Channel cross-correlations are also presented, which can have a significant impact on effectiveness of direct assimilation performance.

instrument calibration↗
NASA NTRS1994

Effects of low sampling rate in the digital data-transition tracking loop

This article describes the performance of the all-digital data-transition tracking loop (DTTL) with coherent and noncoherent sampling using nonlinear theory. The effects of few samples per symbol and of noncommensurate sampling and symbol rates are addressed and analyzed. Their impact on the probability density and variance of the phase error are quantified through computer simulations. It is shown that the performance of the all-digital DTTL approaches its analog counterpart when the sampling and symbol rates are noncommensurate (i.e., the number of samples per symbol is an irrational number). The loop signal-to-noise ratio (SNR) (inverse of phase error variance) degrades when the number of samples per symbol is an odd integer but degrades even further for even integers.

Mileant, A.↗
NASA NTRS1994

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Downie, John D.↗
NASA NTRS1998

Masking by Gratings Predicted by an Image Sequence Discriminating Model: Testing Models for Perceptual Discrimination Using Repeatable Noise

Adding noise to stimuli to be discriminated allows estimation of observer classification functions based on the correlation between observer responses and relevant features of the noisy stimuli. Examples will be presented of stimulus features that are found in auditory tone detection and visual vernier acuity. using the standard signal detection model (Thurstone scaling), we derive formulas to estimate the proportion of the observers decision variable variance that is controlled by the added noise. one is based on the probability of agreement of the observer with him/herself on trials with the same noise sample. Another is based on the relative performance of the observer and the model. When these do not agree, the model can be rejected. A second derivation gives the probability of agreement of observer and model when the observer follows the model except for internal noise. Agreement significantly less than this amount allows rejection of the model.

Ahumada, Albert J., Jr.↗
NASA NTRS1998

Testing Models for Perceptual Discrimination Using Repeatable Noise

Adding noise to stimuli to be discriminated allows estimation of observer classification functions based on the correlation between observer responses and relevant features of the noisy stimuli. Examples will be presented of stimulus features that are found in auditory tone detection and visual Vernier acuity. Using the standard signal detection model (Thurstone scaling), we derive formulas to estimate the proportion of the observer's decision variable variance that is controlled by the added noise. One is based on the probability of agreement of the observer with him/herself on trials with the same noise sample. Another is based on the relative performance of the observer and the model. When these do not agree, the model can be rejected. A second derivation gives the probability of agreement of observer and model when the observer follows the model except for internal noise. Agreement significantly less than this amount allows rejection of the model.

Ahumada, Albert J., Jr.↗
NASA NTRS1995

Allan deviation computations of a linear frequency synthesizer system using frequency domain techniques

Allan Deviation computations of linear frequency synthesizer systems have been reported previously using real-time simulations. Even though it takes less time compared with the actual measurement, it is still very time consuming to compute the Allan Deviation for long sample times with the desired confidence level. Also noises, such as flicker phase noise and flicker frequency noise, can not be simulated precisely. The use of frequency domain techniques can overcome these drawbacks. In this paper the system error model of a fictitious linear frequency synthesizer is developed and its performance using a Cesium (Cs) atomic frequency standard (AFS) as a reference is evaluated using frequency domain techniques. For a linear timing system, the power spectral density at the system output can be computed with known system transfer functions and known power spectral densities from the input noise sources. The resulting power spectral density can then be used to compute the Allan Variance at the system output. Sensitivities of the Allan Variance at the system output to each of its independent input noises are obtained, and they are valuable for design trade-off and trouble-shooting.

Wu, Andy↗
NASA NTRS1983

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗
NASA NTRS1977

Effect of inlet disturbances on fan inlet noise during a static test

Measurements of fan rotor inlet noise taken during static test situations are at variance with aircraft engine flight data. In particular, static tests generally yield a significantly higher tone at blade passage frequency than that measured during flight. To explain this discrepancy, the extent of the influence of inlet ground vortices and large-scale inlet turbulence on the forward-radiated fan noise measured at a static test facility was investigated. While such inlet disturbances were generated intentionally in an anechoic test chamber, far-field acoustic measurements and inlet flow-field hot-film mappings of a fan rotor were obtained. Experimental results indicate that the acoustic effect of such disturbances appears to be less severe for supersonic than for subsonic tip speeds. Further, a reverse flow that occurs on the exterior cowl in static test facilities appears to be an additional prime candidate for creating inlet disturbances and causing variance between flight and static acoustic data.

Bekofske, K. L.↗
NASA NTRS1976

Transient excitation and data processing techniques employing the fast fourier transform for aeroelastic testing

The development of testing techniques useful in airplane ground resonance testing, wind tunnel aeroelastic model testing, and airplane flight flutter testing is presented. Included is the consideration of impulsive excitation, steady-state sinusoidal excitation, and random and pseudorandom excitation. Reasons for the selection of fast sine sweeps for transient excitation are given. The use of the fast fourier transform dynamic analyzer (HP-5451B) is presented, together with a curve fitting data process in the Laplace domain to experimentally evaluate values of generalized mass, model frequencies, dampings, and mode shapes. The effects of poor signal to noise ratios due to turbulence creating data variance are discussed. Data manipulation techniques used to overcome variance problems are also included. The experience is described that was gained by using these techniques since the early stages of the SST program. Data measured during 747 flight flutter tests, and SST, YC-14, and 727 empennage flutter model tests are included.

Jennings, W. P.↗