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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 397 records · Page 22
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NASA NTRS1978

Orbit determination accuracies using satellite-to-satellite tracking

The results are reported of the ATS-6/GEOS-3 and the ATS-6 Nimbus-6 satellite-to-satellite orbit determination experiments. NASA intends to use the tracking data relay satellite system for operational orbit determination of NASA satellites. Hence, in the near future, satellite-to-satellite tracking data will be routinely processed to obtain orbits. The satellite-to-satellite tracking system used in the ATS-6/Nimbus-6 and ATS-6/GEOS-3 experiments performed with a resolution of 1 to 2 m in range and less than 1 mm/s in range rate for a 10-s averaging. A Bayesian least squares estimation technique utilizing independent ranging to the synchronous relay satellite was determined to be the most effective procedure for estimating orbits from satellite-to-satellite tracking data. The use of this technique yields estimates of user satellite orbits which are comparable in accuracy to what is usually obtained from ground based systems.

Vonbun, F. O.↗
NASA NTRS1979

Results of GEOS 3/ATS 6 satellite-to-satellite tracking orbit determination experiment

The purpose of the Geos 3/ATS 6 satellite-to-satellite tracking experiment was to develop, test, and evaluate methods of deriving orbit estimates from satellite-to-satellite tracking data. The results of the form of conventional orbit overlap tests, and a comparison of a Geos 3 orbit estimate obtained from satellite-to-satellite (SST) tracking data with an orbit estimate derived form C-band data. The method recommeded for estimating orbits from SST data is a Bayesian least squares procedure utilizing independent ranging to the relay satellite.

Argentiero, P.↗
NASA NTRS1979

Orbit/attitude estimation with Landsat-1 and -2 landmark data

The accuracy of spacecraft orbit and attitude determination is investigated using Landsat-1 and -2 picture data. The data consists of ground control points, of known geodetic coordinates, which are identified on a series of Landsat pictures. Both sequential (extended Kalman filter) and batch (nonlinear Bayesian weighted least-squares) estimation techniques have been implemented in two software systems. Discussion of these systems includes a system overview, mathematical formulation, and sample numerical results. Particular emphasis is given to the application of a spectral analysis technique to derive spacecraft attitude models.

Hall, D. L.↗
NASA NTRS1979

Applications of estimation theory to inverse problems in meteorology

The paper applies iterated and non-iterated extended Kalman filters to solve two practical meteorological inversion problems. Passive microwave satellite soundings are used to infer vertical temperature profiles and cloud parameters. In both cases it is shown that improvements can be obtained over presently used techniques. Finally, the results suggest that modern multivariate nonlinear recursive estimation techniques based in a Bayesian methodology can be a valuable tool in the area of remote sounding of atmospheric parameters.

Gustafson, D. E.↗
NASA NTRS1978

A computer program for estimation from incomplete multinomial data

Coding is given for maximum likelihood and Bayesian estimation of the vector p of multinomial cell probabilities from incomplete data. Also included is coding to calculate and approximate elements of the posterior mean and covariance matrices. The program is written in FORTRAN 4 language for the Control Data CYBER 170 series digital computer system with network operating system (NOS) 1.1. The program requires approximately 44000 octal locations of core storage. A typical case requires from 72 seconds to 92 seconds on CYBER 175 depending on the value of the prior parameter.

Credeur, K. R.↗
NASA NTRS1980

Differential correction capability of the GTDS using TDRSS data

A differential correction (DC) capability was implemented in the Goddard Trajectory Determination System (GTDS) to process satellite tracking data acquired via the Tracking and Data Relay Satellite System (TRDRSS). Configuration of the TDRSS is reviewed, observation modeling is presented, and major features of the capability are discussed. The following types of TDRSS data can be processed by GTDS: two way relay range and Doppler measurements, hybrid relay range and Doppler measurements, one way relay Doppler measurements, and differenced one way relay Doppler measurements. These data may be combined with conventional ground based direct tracking data. By using Bayesian weighted least squares techniques, the software allows the simultaneous determination of the trajectories of up to four different satellites - one user satellite and three relay satellites. In addition to satellite trajectories, the following parameters can be optionally solved: for drag coefficient, reflectivity of a satellite for solar radiation pressure, transponder delay, station position, and biases.

Liu, S. Y.↗
NASA NTRS1979

Classification results using spacially correlated Landsat data

Tubbs and Coberly (1978) demonstrated that Landsat multispectral scanner data are not independent random observations, but, are in fact highly correlated. They also demonstrated that the correlation structure for the data is similar to that of a stationary autoregressive process of order one. This paper investigates the effect that serially correlated training data have upon both the estimation of parameters and the classification problem. Results are included for both the Bayesian and maximum likelihood classification procedures.

Tubbs, J. D.↗
NASA NTRS1980

Failure detection system design methodology

The design of a failure detection and identification system consists of designing a robust residual generation process and a high performance decision making process. The design of these two processes are examined separately. Residual generation is based on analytical redundancy. Redundancy relations that are insensitive to modelling errors and noise effects are important for designing robust residual generation processes. The characterization of the concept of analytical redundancy in terms of a generalized parity space provides a framework in which a systematic approach to the determination of robust redundancy relations are developed. The Bayesian approach is adopted for the design of high performance decision processes. The FDI decision problem is formulated as a Bayes sequential decision problem. Since the optimal decision rule is incomputable, a methodology for designing suboptimal rules is proposed. A numerical algorithm is developed to facilitate the design and performance evaluation of suboptimal rules.

Chow, E. Y.↗
NASA NTRS1983

Trajectory-Estimation Error Analysis

Orbital and Geodetic Parameter Estimation Error Analysis Program (ORAN) is Bayesian least-squares simulation program for orbital trajectories. ORAN does not process data; rather, computes accuracy of results of data reduction if measurements are processed by minimum-variance data-reduction program. Actual data used to provide time when given measurement was available and estimated noise on that measurement.

Putney, B.↗
NASA NTRS1982

Short-term fluctuations in the eddy heat flux and baroclinic stability of the atmosphere

National Meteorological Center data from midlatitudes for three Januaries is used in calculating time series of the zonal mean meridional eddy heat flux and the zonal mean baroclinic stability, as measured by the difference between the zonal wind shear and the critical value of the shear in two-level models. Time-lagged correlations between the two series reveal a highly significant negative correlation for short time lags, peaking at approximately -0.4 when the stability parameter lags one half day behind the eddy flux. They also reveal that strongly unstable conditions are not followed by significant increases in the eddy flux. These results are seen as indicating that the synoptic variations of the zonal mean eddy flux are not closely related to the degree of baroclinic instability of the zonal mean flow. The autocorrelation of the eddy flux is then compared with those expected for autoregressive processes. A Bayesian information criterion suggests that the behavior is represented best by a damped oscillation, with a damping time of 0.8 day and a period of five days.

Stone, P. H.↗
NASA NTRS1982

The use of baseline measurements and geophysical models for the estimation of crustal deformations and the terrestrial reference system

Four possible estimators are investigated for the monitoring of crustal deformations from a combination of repeated baseline length measurements and adopted geophysical models, particularly an absolute motion plate model. The first estimator is an extension of the familiar free adjustment. The next two are Bayesian type estimators, one weak and one strong. Finally, a weighted constraint estimator is presented. The properties of these four estimators are outlined and their physical interpretations discussed. A series of simulations are performed to test the four estimators and to determine whether or not to incorporate a plate model for the monitoring of deformations. The application of these estimations to the maintenance of a new conventional terrestrial reference system is discussed.

Bock, Y.↗
NASA NTRS1983

Detection and recognition of simple spatial forms

A model of human visual sensitivity to spatial patterns is constructed. The model predicts the visibility and discriminability of arbitrary two-dimensional monochrome images. The image is analyzed by a large array of linear feature sensors, which differ in spatial frequency, phase, orientation, and position in the visual field. All sensors have one octave frequency bandwidths, and increase in size linearly with eccentricity. Sensor responses are processed by an ideal Bayesian classifier, subject to uncertainty. The performance of the model is compared to that of the human observer in detecting and discriminating some simple images.

Watson, A. B.↗
NASA NTRS1982

Research and development of LANDSAT-based crop inventory techniques

A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.

Horvath, R.↗
NASA NTRS1982

Mapping of deciduous forest cover using simulated Landsat-D TM data

An evaluation is presented of the supervised vegetation classification images of heavily forested terrain in the eastern US produced from simulated Landsat-D Thematic Mapper data as part of the Joint NASA/Geosat Test Case study of the Lost River, West Virginia, gas field. This investigation utilized data supplied by the NS-001 aircraft multispectral scanner (15 m IFOV) of NASA. The instruments recognized a total of 9 vegetation classes and one soil class. A hybrid parallelepiped-Bayesian maximum likelihood classifier was employed to produce the supervised vegetation classifications. The data were obtained at the height of the fall foliage display for this portion of West Virginia. Results show that both classifications are highly accurate, based on a comparison of assignment of vegetation classes on each of the images with actual ground conditions. It is noted that the anomalous distribution of certain woody species found in the resulting supervised classifications may be related to the microseepage of methane from the gas reservoir.

Rock, B. N.↗
NASA NTRS1983

Spline Classification Methods

The use of spline functions in the development of classification algorithms is discussed. A method is formulated for producing spline approximations to univariate density functions when each density function is described by a histogram of measurements. The resulting approximations are then incorporated into a Bayesian classification procedure for which the probability of misclassification can be readily computed. Some preliminary numerical results are presented to illustrate the method.

Guseman, L. F., Jr.↗
NASA NTRS1983

Estimating crustal deformations from a combination of baseline measurements and geophysical models

Three possible estimation algorithms are presented for the monitoring of crustal deformations from a combination of repeated baseline measurements and prior deformation information. Attention is given to best linear minimum bias estimation, best linear estimation, and Bayesian estimation. The application of the deformation estimators to the maintenance of a conventional terrestrial reference system is considered. It is shown that if no prior deformation model is available, the free adjustment is the preferred algorithm. In the presence of prior information, however, it is better to use a somewhat incorrect model than to ignore it altogether. The best estimation model of the ones tested is the best linear estimation.

Bock, Y.↗
NASA NTRS1983

The statewide forest/nonforest classification of Pennsylvania using Landsat MSS data

A procedure is described for processing the large volume of data needed to generate a Landsat-derived forest resource map (forest/nonforest mask) for the state of Pennsylvania, for use in a defoliation assessment program. Landsat coverage of the 28 million acres encompassing Pennsylvania requires portions of ten Landsat frames, totalling approximately 76 million pixels. A prime effort of this project was to efficiently and accurately classify this data into forest or nonforest categories. A specialized approach to Bayesian classification was developed which involved the use of MSS5 and MSS7; the identification of a single class, forest; and the use of the confidence map to generate the forest/nonforest mask. Statewide, for 7-acre contiguous forest areas, the overall agreement achieved between the mask and reference data was 90 percent.

Russo, S. A.↗