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Results for “error estimation and analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

The effect of directional radiation models on the interpretation of earth radiation budget measurements

A parameter estimation technique is presented to estimate the radiative flux density distribution over the earth from a set of radiometer measurements at satellite altitude. The technique analyzes measurements from a wide field of view, horizon to horizon, nadir pointing sensor with a mathematical technique to derive the radiative flux density estimates at the top of the atmosphere for resolution elements smaller than the sensor field of view. A computer simulation of the data analysis technique is presented for both earth-emitted and reflected radiation. The errors resulting from the assumed directional radiation model, spatial model and random measurement error have little effect on the global mean radiation. Zonal estimates were found to be more sensitive to the spatial model than to the directional radiation model. Results from analyzing medium field of view measurements showed a much greater sensitivity to the directional radiation model even on a global scale.

Green, R. N.↗
DOE OSTI2024

Analysis of BOSS galaxy data with weighted skew-spectra

We present the first application of the weighted skew-spectra to analyze non-Gaussian information in galaxy survey data. Using the tree-level galaxy skew-spectra together with the one-loop power spectrum multipoles, we analyze the Sloan Digital Sky Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) galaxy clustering data, and target our search towards the equilateral bispectrum shape of primordial non-Gaussianity. We use the Effective Field Theory model for the galaxy power spectrum and bispectrum, and account for systematic effects, such as the survey geometry. From our likelihood analysis, we find f NL equil = -34 +296 -334 at 68% CL, consistent with previous works, while systematic errors from our treatment of the survey geometry lead to an unreliable estimation of f NL ortho . As a result, we further constrain the bias and counterterm parameters, while keeping the cosmology fixed to Planck 2018 values. As a check, we also validate our analysis pipeline using theNseries simulation suite.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Estimation of full modal damping matrices from complex test modes

This paper describes the refinements of a previously published method for estimating a full modal damping matrix from complex test modes. It also documents application of the refined method to a structure where complex test modes were derived by the ERA method from multi-input random vibration test data. A numerical example based on simulated test data is presented to demonstrate the validity of the method. The application using real data was not successful, presumably because of noise in the small phase angles of the measured complex modes. Alternative test and data reduction procedures are suggested as possible remedies to the problem. A careful analysis of measurement and data processing errors should be made to examine basic feasibility before implementing the alternative procedures. The ability to estimate a full modal damping matrix is considered important for the preflight estimation of on-orbit damping, and for the synthesis of structural damping from substructure tests.

Hasselman, T. K.↗
NASA NTRS2004

SIM spectral characteristics and accuracy analysis

The Space Interferometry Mission (SIM) will perform global astrometry (full sky), local wide-angle (15 degree) and narrow-angle (1 degree) observations to search extra-solar planets, and can calibrate stellar and galactic evolution theories. The astrometric accuracy of the SIM mission depends on spectral characteristics of the optics, detectors and targets. This paper will discuss the photometric throughput of the SIM instrument, and analyze effects of wavefront errors, optical mismatches and control biases as a function of wavelength. The color dependence models of the instrument optics including mirrors, lenses, field-stop and beam-splitter are presented. The performances of different detectors with a variety of coatings are compared. A model of the SIM fringe spectrometer is created. For early and late types of stars, brightness dependency errors are analyzed for different combinations of optics and detectors. Visibility loss due to imperfect optics is investigated in detail. Based on the models of instrument and estimated visibilities, the astrometric accuracies for various kinds of stars are evaluated. It is important to emphasize that not only light sources, mirrors, lenses, field stop and detectors are all wavelength dependent, but also fringe visibility loss, wavefront error, optics control error, etc. are all a function of wavelengths. For the first time the estimate of SIM performance is based on spectral analysis of all factors above, rather than monochromatic approximations of detected fringes, or simply adopted constants. This paper summarizes the astrometric accuracies for a wide range of stars and various combinations of optical design and detector configurations. It has been verified that SIM has astrometric accuracy of about 4 μas for targets with different spectra.

Shao, Michael↗
DOE OSTI2020

The arbitrary‐order virtual element method for linear elastodynamics models: convergence, stability and dispersion‐dissipation analysis

Abstract We design the conforming virtual element method for the numerical approximation of the two‐dimensional elastodynamics problem. We prove stability and convergence of the semidiscrete approximation and derive optimal error estimates under h ‐ and p ‐refinement in both the energy and the L 2 norms. The performance of the proposed virtual element method is assessed on a set of different computational meshes, including nonconvex cells up to order four in the h ‐refinement setting. Exponential convergence is also experimentally observed under p ‐refinement. Finally, we present a dispersion‐dissipation analysis for both the semidiscrete and fully discrete schemes, showing that polygonal meshes behave as classical simplicial/quadrilateral grids in terms of dispersion‐dissipation properties.

Antonietti, Paola F.↗
DOE OSTI2020

The arbitrary-order virtual element method for linear elastodynamics models. Convergence, stability and dispersion-dissipation analysis.

We design the conforming virtual element method for the numerical approximation of the two dimensional elastodynamics problem. We prove stability and convergence of the semi-discrete approximation and derive optimal error estimates under $\textit{h}$-refinement in both the energy and the $L^2$ norms, and optimal error estimates under $\textit{p}$-refinement in the energy norm. The performance of the proposed virtual element method is assessed on a set of different computational meshes, including non-convex cells up to order four in the h-refinement setting. Exponential convergence is also experimentally observed under p-refinement. Finally, we present a dispersion-dissipation analysis for both the semi-discrete and fully-discrete schemes, showing that polygonal meshes behave as classical simplicial/quadrilateral grids in terms of dispersion-dissipation properties.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Search and rescue satellite (SARSAT) error analysis of the 406 MHz system

A computer simulation investigated conditions encountered by the SARSAT 406 MHz system. Three and four parameter emergency transmitter (ET) location solutions were determined. Latitude and longitude, a frequency bias, and in the four-parameters solutions, a linear frequency drift term were estimated. Earth gravity, frequency drift, and measurement noise are the major error contributors to the ET position. Time-tag ET height and velocity errors, although significant are not routinely present. In the four-parameter solutions the drift error is eliminated; however, the sensitivity to measurement noise increases. Using the four-parameter pass solutions, the 406 MHz oscillator specifications can be relaxed and still satisfy the 5 km positioning requirement. Since a linear oscillator drift is removed in the four-parameter solution, only the measurement noise over 10-15 min is important.

Yionoulis, S. M.↗
NASA NTRS1986

Static shape control for flexible structures

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

Rodriguez, G.↗
NASA NTRSDate not supplied

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally distributed single-catchment locations for a 10-yr experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF consistently increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone, and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results additionally demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Rolf Reichle↗
NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗
NASA NTRS2023

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally-distributed single-catchment locations for a 10-year experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF systematically increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results also demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Soil moisture↗
DOE OSTI2022

A Statistical Interpolation Code for Ocean Analysis and Forecasting

Abstract We present a data assimilation package for use with ocean circulation models in analysis, forecasting, and system evaluation applications. The basic functionality of the package is centered on a multivariate linear statistical estimation for a given predicted/background ocean state, observations, and error statistics. Novel features of the package include support for multiple covariance models, and the solution of the least squares normal equations either using the covariance matrix or its inverse—the information matrix. The main focus of this paper, however, is on the solution of the analysis equations using the information matrix, which offers several advantages for solving large problems efficiently. Details of the parameterization of the inverse covariance using Markov random fields are provided and its relationship to finite-difference discretizations of diffusion equations are pointed out. The package can assimilate a variety of observation types from both remote sensing and in situ platforms. The performance of the data assimilation methodology implemented in the package is demonstrated with a yearlong global ocean hindcast with a 1/4° ocean model. The code is implemented in modern Fortran, supports distributed memory, shared memory, multicore architectures, and uses climate and forecasts compliant Network Common Data Form for input/output. The package is freely available with an open source license from www.tendral.com/tsis/ .

Srinivasan, Ashwanth↗
NASA NTRS1974

Evaluating the accuracy of selenodesic reference grids

Estimates were made of the accuracy of reference point grids using the technique of calculating the errors from theoretical analysis. Factors taken into consideration were: telescope accuracy, number of photographs, and libration amplitude. To solve the problem, formulas were used for the relationship between the coordinates of lunar surface points and their images on the photograph.

Koptev, A. A.↗
NASA NTRS1984

Multipath induced errors in meteorological Doppler/interferometer location systems

One application of an RF interferometer aboard a low-orbiting spacecraft to determine the location of ground-based transmitters is in tracking high-altitude balloons for meteorological studies. A source of error in this application is reflection of the signal from the sea surface. Through propagating and signal analysis, the magnitude of the reflection-induced error in both Doppler frequency measurements and interferometer phase measurements was estimated. The theory of diffuse scattering from random surfaces was applied to obtain the power spectral density of the reflected signal. The processing of the combined direct and reflected signals was then analyzed to find the statistics of the measurement error. It was found that the error varies greatly during the satellite overpass and attains its maximum value at closest approach. The maximum values of interferometer phase error and Doppler frequency error found for the system configuration considered were comparable to thermal noise-induced error.

Wallace, R. G.↗
NASA NTRS2003

The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

Adler, Robert F.↗
NASA NTRS2007

Safety and Performance Analysis of the Non-Radar Oceanic/Remote Airspace In-Trail Procedure

This document presents a safety and performance analysis of the nominal case for the In-Trail Procedure (ITP) in a non-radar oceanic/remote airspace. The analysis estimates the risk of collision between the aircraft performing the ITP and a reference aircraft. The risk of collision is only estimated for the ITP maneuver and it is based on nominal operating conditions. The analysis does not consider human error, communication error conditions, or the normal risk of flight present in current operations. The hazards associated with human error and communication errors are evaluated in an Operational Hazards Analysis presented elsewhere.

Carreno, Victor A.↗
NASA NTRS2020

Aircraft System Identification from Multisine Inputs and Frequency Responses

A frequency-domain approach is described for estimating parameters, such as stability and control derivatives, in aircraft flight dynamic models from measured input and output data. The approach uses orthogonal phase-optimized multisines for moving the aircraft control effectors, Fourier analysis for computing multiple-input multiple-output frequency responses, and a maximum likelihood estimator called frequency response error (FRE) for determining values and uncertainties for the model parameters. The approach is demonstrated using flight test data for two subscale airplanes: the T-2 generic transport model and the X-56A aeroelastic demonstrator. Results and comparisons with the output-error method indicated that the approach produced accurate estimates of stability and control derivatives and their uncertainties from flight test data.

Grauer, Jared A.↗