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At least 253 records · Page 14

Magnetic field directional discontinuities. I - Minimum variance errors

The paper deals with a statistical analysis of the errors associated with a minimum variance analysis of directional discontinuities by use of an idealized model of these discontinuities and various simulations, and also by an examination of actual Mariner 10 interplanetary magnetic field data. An empirical expression is derived for the magnitude of the error in an estimated discontinuity normal component, relative to the total field across the directional discontinuity. The analysis was performed primarily to aid in differentiating between interplanetary tangential and rotational discontinuities observed by Mariner 10.

Lepping, R. P.↗

Error analysis of bent ray radio occultation measurments

There are two types of experimental measurement errors of the Doppler data associated with the radio occultation, random and systematic. Random errors are due to thermal noise in the transmission channel, and the phase lock loop, and quantization error in the digital circuitry. These are called noise type errors. The systematic errors are due to geometric uncertainty and equipment phase instability. Considered is the amount of uncertainty, due to random measurement errors, in the refractivity profiles reconstructed by this type of indirect sensing experiment. A class of refractivity profiles is defined which approximately fit the set of measured data. Bounds are placed on the extent of this class of solution profiles. To accomplish this, the sensivity of the reconstructed refractivity profiles to errors in the measured quantity and the statistics of the errors in the measurement are examined.

Saintgermain, R. L.↗

Analyst variability in labeling of unsupervised classifications

Analyst variability in the labeling of unsupervised classifications is tested for Landsat 5 Thematic Mapper image products covering two test sites in southern California. The accuracy of results are tested using samples from a photo interpreted base map of the area. The significance of differences between analysts is indicated by comparing Kappa statistics derived from error matrices. Analyst variability is found to be statistically significant in most cases. Certain analysts provided consistently better results for a given study area or degree of training. This work demonstrates the potential influence of analyst bias on what would otherwise seem to be a fairly objective method and suggests that controls for this subjectivity should be factored into experimental designs.

Mcgwire, Kenneth C.↗

Optimal GSTDN/TDRSS bit error rate evaluation using limited sample sizes

Statistical studies of telemetry errors were made on data from the Solar Mesosphere Explorer (SME). Examination of frame sync words, as received at the ground station, indicated a wide spread of Bit Error Rates (BER) among stations. A study of the distribution of errors per station pass, however, showed that there was a tendency for the station software to add an even number of spurious errors to the count. A count of wild points in science data, rejecting drop-outs and other system errors, yielded an average random BER of 3.1 x 10 to the -6 with 99% confidence limits of 2.6 and 3.8 x 10 to the -6. The system errors are typically 5 to 100 times more frequent than the truly random errors.

Coffey, R. E.↗

Sensitivity analysis of helicopter IMC decelerating steep approach and landing performance to navigation system parameters

Results of a study to investigate, by means of a computer simulation, the performance sensitivity of helicopter IMC DSAL operations as a function of navigation system parameters are presented. A mathematical model representing generically a navigation system is formulated. The scenario simulated consists of a straight in helicopter approach to landing along a 6 deg glideslope. The deceleration magnitude chosen is 03g. The navigation model parameters are varied and the statistics of the total system errors (TSE) computed. These statistics are used to determine the critical navigation system parameters that affect the performance of the closed-loop navigation, guidance and control system of a UH-1H helicopter.

Karmali, M. S.↗

Bayes Error Rate Estimation Using Classifier Ensembles

The Bayes error rate gives a statistical lower bound on the error achievable for a given classification problem and the associated choice of features. By reliably estimating th is rate, one can assess the usefulness of the feature set that is being used for classification. Moreover, by comparing the accuracy achieved by a given classifier with the Bayes rate, one can quantify how effective that classifier is. Classical approaches for estimating or finding bounds for the Bayes error, in general, yield rather weak results for small sample sizes; unless the problem has some simple characteristics, such as Gaussian class-conditional likelihoods. This article shows how the outputs of a classifier ensemble can be used to provide reliable and easily obtainable estimates of the Bayes error with negligible extra computation. Three methods of varying sophistication are described. First, we present a framework that estimates the Bayes error when multiple classifiers, each providing an estimate of the a posteriori class probabilities, a recombined through averaging. Second, we bolster this approach by adding an information theoretic measure of output correlation to the estimate. Finally, we discuss a more general method that just looks at the class labels indicated by ensem ble members and provides error estimates based on the disagreements among classifiers. The methods are illustrated for artificial data, a difficult four-class problem involving underwater acoustic data, and two problems from the Problem benchmarks. For data sets with known Bayes error, the combiner-based methods introduced in this article outperform existing methods. The estimates obtained by the proposed methods also seem quite reliable for the real-life data sets for which the true Bayes rates are unknown.

Tumer, Kagan↗

Compact disk error measurements

The objectives of this project are as follows: provide hardware and software that will perform simple, real-time, high resolution (single-byte) measurement of the error burst and good data gap statistics seen by a photoCD player read channel when recorded CD write-once discs of variable quality (i.e., condition) are being read; extend the above system to enable measurement of the hard decision (i.e., 1-bit error flags) and soft decision (i.e., 2-bit error flags) decoding information that is produced/used by the Cross Interleaved - Reed - Solomon - Code (CIRC) block decoder employed in the photoCD player read channel; construct a model that uses data obtained via the systems described above to produce meaningful estimates of output error rates (due to both uncorrected ECC words and misdecoded ECC words) when a CD disc having specific (measured) error statistics is read (completion date to be determined); and check the hypothesis that current adaptive CIRC block decoders are optimized for pressed (DAD/ROM) CD discs. If warranted, do a conceptual design of an adaptive CIRC decoder that is optimized for write-once CD discs.

Howe, D.↗

Application of a Monte Carlo accuracy assessment tool to TDRS and GPS

In support of a NASA study on the application of radio interferometry to satellite orbit determination, MITRE developed a simulation tool for assessing interferometric tracking accuracy. Initially, the tool was applied to the problem of determining optimal interferometric station siting for orbit determination of the Tracking and Data Relay Satellite (TDRS). Subsequently, the Orbit Determination Accuracy Estimator (ODAE) was expanded to model the general batch maximum likelihood orbit determination algorithms of the Goddard Trajectory Determination System (GTDS) with measurement types including not only group and phase delay from radio interferometry, but also range, range rate, angular measurements, and satellite-to-satellite measurements. The user of ODAE specifies the statistical properties of error sources, including inherent observable imprecision, atmospheric delays, station location uncertainty, and measurement biases. Upon Monte Carlo simulation of the orbit determination process, ODAE calculates the statistical properties of the error in the satellite state vector and any other parameters for which a solution was obtained in the orbit determination. This paper presents results from ODAE application to two different problems: (1)determination of optimal geometry for interferometirc tracking of TDRS, and (2) expected orbit determination accuracy for Global Positioning System (GPS) tracking of low-earth orbit (LEO) satellites. Conclusions about optimal ground station locations for TDRS orbit determination by radio interferometry are presented, and the feasibility of GPS-based tracking for IRIDIUM, a LEO mobile satellite communications (MOBILSATCOM) system, is demonstrated.

Pavloff, Michael S.↗

Debris Flux Comparisons From The Goldstone Radar, Haystack Radar, and Hax Radar Prior, During, and After the Last Solar Maximum

The continual monitoring of low Earth orbit (LEO) debris environment using highly sensitive radars is essential for an accurate characterization of these dynamic populations. Debris populations are continually evolving since there are new debris sources, previously unrecognized debris sources, and debris loss mechanisms that are dependent on the dynamic space environment. Such radar data are used to supplement, update, and validate existing orbital debris models. NASA has been utilizing radar observations of the debris environment for over a decade from three complementary radars: the NASA JPL Goldstone radar, the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar), and the MIT/LL Haystack Auxiliary radar (HAX). All of these systems are highly sensitive radars that operate in a fixed staring mode to statistically sample orbital debris in the LEO environment. Each of these radars is ideally suited to measure debris within a specific size region. The Goldstone radar generally observes objects with sizes from 2 mm to 1 cm. The Haystack radar generally measures from 5 mm to several meters. The HAX radar generally measures from 2 cm to several meters. These overlapping size regions allow a continuous measurement of cumulative debris flux versus diameter from 2 mm to several meters for a given altitude window. This is demonstrated for all three radars by comparing the debris flux versus diameter over 200 km altitude windows for 3 nonconsecutive years from 1998 through 2003. These years correspond to periods before, during, and after the peak of the last solar cycle. Comparing the year to year flux from Haystack for each of these altitude regions indicate statistically significant changes in subsets of the debris populations. Potential causes of these changes are discussed. These analysis results include error bars that represent statistical sampling errors, and are detailed in this paper.

Stokely, C. L.↗

Burst-error characteristics of the equatorial transionospheric channel

Analyses of AGC analog data from the Small Astronomy Satellite (SAS) at VHF (136 MHz) have shown amplitude fluctuations in the signals received at several equatorial tracking sites operated by NASA. Errors in data are shown to increase markedly for nighttime satellite passes around the periods of the two equinoxes as compared to the errors observed during other periods. Qualitative and quantitative correlations are established between the ionospheric scintillation phenomenon and the occurrence of errors. Strong time and geographic cause-and-effect relationships are established by determining the statistical correlation between scintillation indices and bit error rates. Detailed analyses of the AGC fading statistics and the fine grain error statistics, such as the block-error distribution and the bit-error autocorrelation function, establish the strong correlation between deep fades and their effects on the burst error structure associated with the transionospheric channel and the communication receiver being employed.

Blank, H. A.↗

Optimal wavefront control for adaptive segmented mirrors

A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.

Downie, John D.↗

Prediction of pilot reserve attention capacity during air-to-air target tracking

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

Onstott, E. D.↗

The Application of Probabilistic Methods to the Mistuning Problem

FMM is a reduced order model for efficiently calculating the forced response of a mistuned bladed disk. FMM ID is a companion program which determines the mistuning in a particular rotor. Together, these methods provide a way to acquire data on the mistuning in a population of bladed disks, and then simulate the forced response of the fleet. This process is tested experimentally, and the simulated results are compared with laboratory measurements of a fleet of test rotors. The method is shown to work quite well. It is found that accuracy of the results depends on two factors: the quality of the statistical model used to characterize mistuning, and how sensitive the system is to errors in the statistical modeling.

Griffin, J. H.↗

Uncertainty Estimates for Sonic-Boom Pressure Signatures and Loudness Carpets

A non-intrusive uncertainty quantification method is applied to computational analysis of supersonic, low-boom aircraft. The mean and standard deviation statistics of the pressure waveforms and loudness metrics are evaluated through use of numerical quadrature. The probability density function (p.d.f.) of these outputs is evaluated via kernel density estimation. The simulations use an inviscid, embedded-boundary Cartesian-mesh flow solver in the nearfield combined with an augmented Burgers’ equation solver for propagation in the farfield. The results show that the p.d.f. of the waveform is bimodal at shocks, which makes the mean and standard deviation statistics inappropriate. Despite this limitation, we show that the moment statistics can provide effective assessment of discrepancies when comparing with experimental data. This is demonstrated by presenting uncertainty analysis of a wind-tunnel test and showing that we significantly improve the predictions when we include the test uncertainties in the simulation. Normal distributions are obtained for the ground signature and loudness metrics, which is primarily due to the careful shaping of the low-boom waveform. Separation of variables and error control are used to reduce computational cost. We demonstrate that this is an efficient approach in the sense of balancing numerical errors in the statistics quadrature with discretization errors in the solvers.

ARMD↗

Landsat-8 TIRS Thermal Radiometric Calibration Status

The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11,2013 through March 5,2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side(March 5,2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K).This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.

Julia A Barsi↗

Forecasts of time averages with a numerical weather prediction model

Forecasts of time averages of 1-10 days in duration by an operational numerical weather prediction model are documented for the global 500 mb height field in spectral space. Error growth in very idealized models is described in order to anticipate various features of these forecasts and in order to anticipate what the results might be if forecasts longer than 10 days were carried out by present day numerical weather prediction models. The data set for this study is described, and the equilibrium spectra and error spectra are documented; then, the total error is documented. It is shown how forecasts can immediately be improved by removing the systematic error, by using statistical filters, and by ignoring forecasts beyond about a week. Temporal variations in the error field are also documented.

Roads, J. O.↗

Fundamental Mistuning Model for Probabilistic Analysis Studied Experimentally

The Fundamental Mistuning Model (FMM) is a reduced-order model for efficiently calculating the forced response of a mistuned bladed disk. FMM ID is a companion program that determines the mistuning in a particular rotor. Together, these methods provide a way to acquire mistuning data in a population of bladed disks and then simulate the forced response of the fleet. This process was tested experimentally at the NASA Glenn Research Center, and the simulated results were compared with laboratory measurements of a "fleet" of test rotors. The method was shown to work quite well. It was found that the accuracy of the results depends on two factors: (1) the quality of the statistical model used to characterize mistuning and (2) how sensitive the system is to errors in the statistical modeling.

Griffin, Jerry H.↗