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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Computer-based classification accuracy due to the spatial resolution using per-point versus per-field classification techniques

Data sets simulating three different spatial resolutions (SR's) are computed from data with a 15-m nominal SR that were obtained with NASA's Thermatic Mapper Simulator from an altitude of about 6 km. The classification accuracies (CA's) achieved with the data of each of the four different SR's using a per-point Gaussian maximum likelihood classifier (GMLC) are intercompared. The CA's obtained using simulated 30-m SR data with the per-point GMLC are compared with the CA's achieved with a per-field classifier. It is found that: (1) the use of successively higher SR data resulted in lower overall CA's for classifications with the per-point GMLC, especially in cover classes associated with relatively higher spectral variability across adjacent pixels; (2) higher CA's were achieved using the per-field classifier with 30-m SR data than were achieved with the per-point GMLC; and (3) the largest increases in CA's were achieved with the per-field classifier in cover classes associated with relatively high levels of spectral variability across adjacent pixels.

Latty, R. S.↗
NASA NTRS1982

Modeling methodology for MLS range navigation system errors using flight test data

Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.

Karmali, M. S.↗
NASA NTRS1982

Modulation/demodulation techniques for satellite communications. Part 3: Advanced techniques. The nonlinear channel

A theory for deducing and predicting the performance of transmitter/receivers for bandwidth efficient modulations suitable for use on the nonlinear satellite channel is presented. The underlying principle used throughout is the development of receiver structures based on the maximum likelihood decision rule and aproximations to it. The bit error probability transfer function bounds developed in great detail in Part 4 is applied to these modulation/demodulation techniques. The effects of the various degrees of receiver mismatch are considered both theoretically and by numerous illustrative examples.

Omura, J. K.↗
NASA NTRS1982

Crop proportion estimation problems in AgRISTARS

Some mathematical/statistical problems within the AgRISTARS program amendable to investigations involving the use of surface fitting techniques are overviewed. The Bayes and maximum likelihood rules, bias determination, regression estimators, parameter estimation, and classifier design are addressed.

Heydorn, R. P.↗
NASA NTRS1983

The application of parameter estimation to flight measurements to obtain lateral-directional stability derivatives of an augmented jet-flap STOL airplane

Flight experiments with an augmented jet flap STOL aircraft provided data from which the lateral directional stability and control derivatives were calculated by applying a linear regression parameter estimation procedure. The tests, which were conducted with the jet flaps set at a 65 deg deflection, covered a large range of angles of attack and engine power settings. The effect of changing the angle of the jet thrust vector was also investigated. Test results are compared with stability derivatives that had been predicted. The roll damping derived from the tests was significantly larger than had been predicted, whereas the other derivatives were generally in agreement with the predictions. Results obtained using a maximum likelihood estimation procedure are compared with those from the linear regression solutions.

Stephenson, J. D.↗
NASA NTRS1981

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed.

Hoffer, R. M.↗
NASA NTRS1983

A Bayesian modification to the Jelinski-Moranda software reliability growth model

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed.

Littlewood, B.↗
NASA NTRS1981

Off-nadir antenna bias correction using Amazon rain forest sigma deg data

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Ocean Satellite System (NOSS). Backscattering observations made by the SEASAT-1 scatterometer system show the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which is insensitive to polarization. The variation with angle of incidence may be adequately modeled as sigma deg (dB) = alpha theta + beta with typical values for the incidence-angle coefficient from 0.07 dB deg to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum likelihood estimation algorithms are presented which permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed.

Birrer, I. J.↗
NASA NTRS1981

Use of collateral information to improve LANDSAT classification accuracies

Methods to improve LANDSAT classification accuracies were investigated including: (1) the use of prior probabilities in maximum likelihood classification as a methodology to integrate discrete collateral data with continuously measured image density variables; (2) the use of the logit classifier as an alternative to multivariate normal classification that permits mixing both continuous and categorical variables in a single model and fits empirical distributions of observations more closely than the multivariate normal density function; and (3) the use of collateral data in a geographic information system as exercised to model a desired output information layer as a function of input layers of raster format collateral and image data base layers.

Strahler, A. H.↗
NASA NTRS1981

Recent developments with the ORSER system

Additions to the ORSER remote sensing data processing package are described. The ORSER package consists of about 35 individual programs that are grouped into preprocessing, data analysis, and display subsystems. Additional data formats and data management, data transformation, and geometric correlation programs were supplemented to the preprocessing subsystem. Enhancements to the data analysis techniques include a maximum likelihood classifier (MAXCLASS) and a new version of the STATS program which makes delineation of training areas easier and allows for detection of outlier points. Ongoing developments are also described.

Baumer, G. M.↗
NASA NTRS1981

The evaluation of alternate methodologies for land cover classification in an urbanizing area

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Smekofski, R. M.↗
NASA NTRS1982

Off-nadir antenna bias correction using Amazon rain sigma(0) data

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Oceanic Satellite System (NOSS). Backscattering observations made by the SEASAT Scatterometer System (SASS) showed the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which was insensitive to polarization. The variation with angle of incidence was adequately modeled as scattering coefficient (dB) = a theta b with typical values for the incidence-angle coefficient from 0.07 to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum-likelihood estimation algorithms presented here permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed.

Birrer, I. J.↗
NASA NTRS1982

Identification and control of spacecraft

Information on the identification and control of spacecraft is given. Maximum likelihood estimation, identification accuracy issues, steady state identifiability analysis and stochastic error with process noise are among the topics addressed.

Greene, C. S.↗
NASA NTRS1983

On parameter identification for large space structures

The design of a controller for large space structures (LSS) based on the LQG theory requires the knowledge of the LSS parameters. Since apriori knowledge of the parameters is usually not reliable, the parameters must be identified prior to the controller synthesis, using methods such as the maximum likelihood technique. An expression is obtained for the Fisher information matrix for LSS, from which Cramer-Rao bounds can be obtained in order to determine the accuracy with which the parameters can be identified.

Joshi, S. M.↗
NASA NTRS1983

Atmospheric correction analysis on LANDSAT data over the Amazon region

The Amazon Region natural resources were studied in two ways and compared. A LANDSAT scene and its attributes were selected, and a maximum likelihood classification was made. The scene was atmospherically corrected, taking into account Amazonic peculiarities revealed by (ground truth) of the same area, and the subsequent classification. Comparison shows that the classification improves with the atmospherically corrected images.

Parada, N. D. J.↗
NASA NTRS1983

Establishment of a center of excellence for applied mathematical and statistical research

The state of the art was assessed with regards to efforts in support of the crop production estimation problem and alternative generic proportion estimation techniques were investigated. Topics covered include modeling the greeness profile (Badhwarmos model), parameter estimation using mixture models such as CLASSY, and minimum distance estimation as an alternative to maximum likelihood estimation. Approaches to the problem of obtaining proportion estimates when the underlying distributions are asymmetric are examined including the properties of Weibull distribution.

Woodward, W. A.↗