Search NASA⌕ Search

SEARCH · Search NASA

Results for “modeling and filtering”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

The human as supervisor in automated systems

This hierarchical approach to information display forces the development of a set of human oriented system models which will guide the design of the displays. If the appropriate information is provided at the appropriate time, it is likely that less information will be displayed at any given time, and the quality of the displayed information will require less operator effort to integrate into an assimilatable form. A problem with contemporary control rooms is that there is too much information for an operator to be able to assimilate quickly, easily, and accurately. It is suggested that necessary direction for research in the area of automated control room design is to develop displays which provide active decision aiding for the modern controller. Displays are needed which provide information compatible with the operator's current internal model, filter out irrelevant information, and summarize and condense lower level information.

Mitchell, C. M.↗
NASA NTRS1983

The Mimas ghost revisited - An analysis of the electron flux and electron microsignatures observed in the vicinity of Mimas at Saturn

An analysis of the electron-absorption signature observed by the cosmic-ray system on Voyager 2 near the orbit of Mimas is presented. It is found that these observations cannot be explained as the absorption signature of Mimas. By combining Pioneer 11 and Voyager 2 measurements of the electron flux at Mimas's orbit (L = 3.1), an electron spectrum is found in which most of the flux above about 100 keV is concentrated near 1 to 3 MeV. This spectral form is qualitatively consistent with the bandpass filter model of Van Allen et al. (1980). The expected Mimas absorption signature is calculated from this spectrum neglecting radial diffusion. Since no Mimas absorption signature was observed in the inbound Voyager 2 data, a lower limit on the diffusion coefficient for MeV electrons at L = 3.1 of D greater than 10 to the -8th sq Saturn radii/sec is obtained. With a diffusion coefficient this large, both the Voyager 2 and the Pioneer 11 small-scale electron-absorption-signature observations in Mimas's orbit are enigmatic. Thus the mechanism for producing these signatures is referred to as the Mimas ghost. A cloud of material in orbit with Mimas may account for the observed electron signature if the cloud is at least 1-percent opaque to electrons across a region extending over a few hundred kilometers.

Chenette, D. L.↗
NASA NTRS1985

A preliminary evaluation of the generalized likelihood ratio for detecting and identifying control element failures in a transport aircraft

The application of the Generalized Likelihood Ratio technique to the detection and identification of aircraft control element failures has been evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 aircraft. Simulation results show that the technique has potential but that the effects of wind turbulence and Kalman filter model errors are problems which must be overcome.

Bundick, W. T.↗
NASA NTRS1988

Real-time speech encoding based on Code-Excited Linear Prediction (CELP)

This paper reports on the work proceeding with regard to the development of a real-time voice codec for the terrestrial and satellite mobile radio environments. The codec is based on a complexity reduced version of code-excited linear prediction (CELP). The codebook search complexity was reduced to only 0.5 million floating point operations per second (MFLOPS) while maintaining excellent speech quality. Novel methods to quantize the residual and the long and short term model filters are presented.

Leblanc, Wilfrid P.↗
NASA NTRS1989

CSI compensation for reduced-order model based control of a flexible robot manipulator

In controller design for flexible structures, certain system modes are extremely important for the overall performance of the structure. A reduced-order model (ROM) based control focuses on these modes, providing a viable, active control algorithm for large systems. Unfortunately, unmodeled structure dynamics can interact with the ROM controller (CSI) and cause crippling deterioration of system performance, possibly to the point that system stability is lost. A residual model filter (RMF) eliminates one channel of control structure interaction (CSI), while adding only a simple, second-order filter to the control loop. Thus, the ROM controller can be designed independently, based strictly on performance criteria, and residual mode filters can then be selected to compensate for CSI. A flexible robot manipulator is used for preliminary experimentation with the ROM/RMF design methodology. Since the controller was to be implemented both with, and without compensation for CSI, the ROM control gains are carefully chosen such that closed loop stability is never compromised. In this way, RMF effectiveness is easily evaluated in terms of the improvement in system performance resulting from CSI compensation.

Reisenauer, Brian T.↗
NASA NTRS1994

Enhanced orbit determination filter sensitivity analysis: Error budget development

An error budget analysis is presented which quantifies the effects of different error sources in the orbit determination process when the enhanced orbit determination filter, recently developed, is used to reduce radio metric data. The enhanced filter strategy differs from more traditional filtering methods in that nearly all of the principal ground system calibration errors affecting the data are represented as filter parameters. Error budget computations were performed for a Mars Observer interplanetary cruise scenario for cases in which only X-band (8.4-GHz) Doppler data were used to determine the spacecraft's orbit, X-band ranging data were used exclusively, and a combined set in which the ranging data were used in addition to the Doppler data. In all three cases, the filter model was assumed to be a correct representation of the physical world. Random nongravitational accelerations were found to be the largest source of error contributing to the individual error budgets. Other significant contributors, depending on the data strategy used, were solar-radiation pressure coefficient uncertainty, random earth-orientation calibration errors, and Deep Space Network (DSN) station location uncertainty.

Estefan, J. A.↗
NASA NTRS1997

Response Classification Images in Vernier Acuity

Orientation selective and local sign mechanisms have been proposed as the basis for vernier acuity judgments. Linear image features contributing to discrimination can be determined for a two choice task by adding external noise to the images and then averaging the noises separately for the four types of stimulus/response trials. This method is applied to a vernier acuity task with different spatial separations to compare the predictions of the two theories. Three well-practiced observers were presented around 5000 trials of a vernier stimulus consisting of two dark horizontal lines (5 min by 0.3 min) within additive low-contrast white noise. Two spatial separations were tested, abutting and a 10 min horizontal separation. The task was to determine whether the target lines were aligned or vertically offset. The noises were averaged separately for the four stimulus/response trial types (e.g., stimulus = offset, response = aligned). The sum of the two 'not aligned' images was then subtracted from the sum of the 'aligned' images to obtain an overall image. Spatially smoothed images were quantized according to expected variability in the smoothed images to allow estimation of the statistical significance of image features. The response images from the 10 min separation condition are consistent with the local sign theory, having the appearance of two linear operators measuring vertical position with opposite sign. The images from the abutting stimulus have the same appearance with the two operators closer together. The image predicted by an oriented filter model is similar, but has its greatest weight in the abutting region, while the response images fall to nonsignificance there. The response correlation image method, previously demonstrated for letter discrimination, clarifies the features used in vernier acuity.

Ahumada, Albert J., Jr.↗
NASA NTRS2005

Spatial orientation of optokinetic nystagmus and ocular pursuit during orbital space flight

On Earth, eye velocity of horizontal optokinetic nystagmus (OKN) orients to gravito-inertial acceleration (GIA), the sum of linear accelerations acting on the head and body. We determined whether adaptation to micro-gravity altered this orientation and whether ocular pursuit exhibited similar properties. Eye movements of four astronauts were recorded with three-dimensional video-oculography. Optokinetic stimuli were stripes moving horizontally, vertically, and obliquely at 30 degrees/s. Ocular pursuit was produced by a spot moving horizontally or vertically at 20 degrees/s. Subjects were either stationary or were centrifuged during OKN with 1 or 0.5 g of interaural or dorsoventral centripetal linear acceleration. Average eye position during OKN (the beating field) moved into the quick-phase direction by 10 degrees during lateral and upward field movement in all conditions. The beating field did not shift up during downward OKN on Earth, but there was a strong upward movement of the beating field (9 degrees) during downward OKN in the absence of gravity; this likely represents an adaptation to the lack of a vertical 1-g bias in-flight. The horizontal OKN velocity axis tilted 9 degrees in the roll plane toward the GIA during interaural centrifugation, both on Earth and in space. During oblique OKN, the velocity vector tilted towards the GIA in the roll plane when there was a disparity between the direction of stripe motion and the GIA, but not when the two were aligned. In contrast, dorsoventral acceleration tilted the horizontal OKN velocity vector 6 degrees in pitch away from the GIA. Roll tilts of the horizontal OKN velocity vector toward the GIA during interaural centrifugation are consistent with the orientation properties of velocity storage, but pitch tilts away from the GIA when centrifuged while supine are not. We speculate that visual suppression during OKN may have caused the velocity vector to tilt away from the GIA during dorsoventral centrifugation. Vertical OKN and ocular pursuit did not exhibit orientation toward the GIA in any condition. Static full-body roll tilts and centrifugation generating an equivalent interaural acceleration produced the same tilts in the horizontal OKN velocity before and after flight. Thus, the magnitude of tilt in OKN velocity was dependent on the magnitude of interaural linear acceleration, rather than the tilt of the GIA with regard to the head. These results favor a 'filter' model of spatial orientation in which orienting eye movements are proportional to the magnitude of low frequency interaural linear acceleration, rather than models that postulate an internal representation of gravity as the basis for spatial orientation.

Flight Experiment↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Navagation↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

n/a↗
NASA NTRS2013

Dawn Orbit Determination Team : Trajectory Modeling and Reconstruction Processes at Vesta

The NASA Dawn spacecraft was launched on September 27, 2007 on a mission to study the asteroid belt's two largest objects, Vesta and Ceres. It is the first deep space orbiting mission to demonstrate solar-electric ion propulsion, providing the necessary delta-V to enable capture and escape from two extraterrestrial bodies. At this time, Dawn has completed its science campaign at Vesta and is currently on its journey to Ceres, where it will arrive in mid-2015. The spacecraft spent over a year in orbit around Vesta from July 2011 through August 2012, capturing science data during four dedicated orbit phases. In order to maintain the reference orbits necessary for science and enable the transfers between those orbits, precise and timely orbit determination was required. The constraints associated with low-thrust ion propulsion coupled with the relatively unknown a priori gravity and rotation models for Vesta presented unique challenges for the Dawn orbit determination team. While [1] discusses the prediction performance of the orbit determination products, this paper discusses the dynamics models, filter configuration, and data processing implemented to deliver a rapid orbit determination capability to the Dawn project.

Vesta↗
NASA NTRS2018

A Survey of Methods for Computing Best Estimates of Endoatmospheric and Exoatmospheric Trajectories

Beginning with the mathematical prediction of planetary orbits in the early seventeenth century up through the most recent developments in sensor fusion methods, many techniques have emerged that can be employed on the problem of endo and exoatmospheric trajectory estimation. Although early methods were ad hoc, the twentieth century saw the emergence of many systematic approaches to estimation theory that produced a wealth of useful techniques. The broad genesis of estimation theory has resulted in an equally broad array of mathematical principles, methods and vocabulary. Among the fundamental ideas and methods that are briefly touched on are batch and sequential processing, smoothing, estimation, and prediction, sensor fusion, sensor fusion architectures, data association, Bayesian and non Bayesian filtering, the family of Kalman filters, models of the dynamics of the phases of a rocket's flight, and asynchronous, delayed, and asequent data. Along the way, a few trajectory estimation issues are addressed and much of the vocabulary is defined.

Bernard, William P.↗
NASA NTRS1981

Alterations of the climate of a primitive equation model produced by filtering approximations and subsequent tuning and stochastic forcing

A comparison is made of the simulated climates of nonlinear models based on the primitive equations (PE), balance equations (BE), and quasi-geostrophic (QG) equations. The models and numerical procedures are identical in all possible respects. The models are highly truncated spectral forms of Lorenz's (1960) energy preserving two-layer model. Two means of making use of the information contained in the (presumed known) short-term prediction error statistics are investigated. An unrealistically high level of thermal forcing is used so that the model climates are sufficiently different to allow any improvements due to the empirical methods to be observed. The general tuning problem is outlined and the QG model is tuned, using data obtained from a PE model run, to minimize the mean squared short term prediction error.

Hoffman, R. N.↗
NASA NTRS2021

Geomagnetic Secular Variation Forecast using the NASA GEMS Ensemble Kalman filter: A Candidate SV Model for IGRF‑13

We have produced a 5-year mean secular variation (SV ) of the geomagnetic field for the period 2020–2025. We use the NASA Geomagnetic Ensemble Modeling System (GEMS), which consists of the NASA Goddard geodynamo model and ensemble Kalman filter (EnKF) with 400 ensemble members. Geomagnetic field models are used as observations for the assimilation, including gufm1 (1590–1960), CM4 (1961–2000) and CM6 (2001–2019). The forecast involves a bias correction scheme that assumes that the model bias changes on timescales much longer than the forecast period, so that they can be removed by successive forecast series. The algorithm was validated on the time period 2010-2015 by comparing with CM6 before being applied to the 2020–2025 time period. This forecast has been sub-mitted as a candidate predictive model of IGRF-13 for the period 2020–2025.

Andrew Tangborn↗
NASA NTRS1981

Geomagnetic modeling by optimal recursive filtering

The results of a preliminary study to determine the feasibility of using Kalman filter techniques for geomagnetic field modeling are given. Specifically, five separate field models were computed using observatory annual means, satellite, survey and airborne data for the years 1950 to 1976. Each of the individual field models used approximately five years of data. These five models were combined using a recursive information filter (a Kalman filter written in terms of information matrices rather than covariance matrices.) The resulting estimate of the geomagnetic field and its secular variation was propogated four years past the data to the time of the MAGSAT data. The accuracy with which this field model matched the MAGSAT data was evaluated by comparisons with predictions from other pre-MAGSAT field models. The field estimate obtained by recursive estimation was found to be superior to all other models.

Gibbs, B. P.↗