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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Estimation of the thickness of the Tharsis lava flows and implications for the nature of the topography of the Tharsis plateau

An attempt to estimate the thickness of the volcanics which cover the large part of the Tharsis region is reported. Estimates for the thickness of the flows were made using the numerous occurrences of the partially buried craters throughout the region and a relation between the crater diameter and crater rim height. Estimates were made along the southern contact with the heavily cratered terrain in the Phoenicis Lacus and Memnonia quadrangles, and along the northeast contact with older plains units in the Tharsis and Lunae Palus quadrangles. In these distal regions the thickness estimates range from 0 to 600-700 m of lava. This would indicate that only 20-30% of the topography is the result of volcanic construction. If the 20-30% estimate is representative of Tharsis as a whole then lava thickness would reach only 2-3 km near the center of the region. Thus only a small fraction of the topography presently observed can be attributed to units readily identifiable as volcanic. This additional evidence indicates that the model for Tharsis of a pre-existing elevated region of heavily cratered crust, capped by a veneer of volcanics is correct.

Plescia, J. B.↗
NASA NTRS1981

Evaluation of large area crop estimation techniques

The performance of the USDAs EDITOR system is evaluated. The system processes Landsat imagery and estimates crop hectarage for large areas based on a regression estimator developed on a sample with known ground truth. It is found that use of multitemporal data over unitemporal significantly improves the hectarage estimates, and a 15% reduction in the r-squared of the regression occurs when independent and jackknifed test sets are used to evaluate the performance of the estimator. When an alternative clustering algorithm, CLASSY, is substituted for the current EDITOR method, estimator performance is improved with reduced need for analyst decisions. It is recommended that the CLASSY clustering algorithm and some form of jackknifing be implemented on EDITOR.

Amis, M. L.↗
NASA NTRS1981

The effects of missing data on global ozone estimates

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

Drewry, J. W.↗
NASA NTRS1982

Friction estimation technique for Galileo scan platform control

A friction estimation technique has been developed for the scan platform control of the Galileo spacecraft. The purpose of the estimation is to reduce the impact of friction in the scan platform actuator on the pointing performance of the scan platform so that tight pointing requirements can be met. The estimator operates by comparing the actual behavior of the platform with the expected behavior and attributing the difference to the presence of friction. The estimator is coupled with a proportional-integral-derivative controller to generate a control torque for the scan platform actuator. Since the algorithm will be implemented on an onboard digital computer, a stability analysis of the estimator-controller in discrete time is presented. The performance of the design is demonstrated by a sample slew test case.

Chodas, J. L.↗
NASA NTRS1982

Applications of parameter estimation in the study of spinning airplanes

Spinning airplanes offer challenges to estimating dynamic parameters because of the nonlinear nature of the dynamics. In this paper, parameter estimation techniques are applied to spin flight test data for estimating the error in measuring post-stall angles of attack, deriving Euler angles from angular velocity data, and estimating nonlinear aerodynamic characteristics. The value of the scale factor for post-stall angles of attack agrees closely with that obtained from special wind-tunnel tests. The independently derived Euler angles are seen to be valid in spite of steep pitch angles. Estimates of flight derived nonlinear aerodynamic parameters are evaluated in terms of the expected fit error.

W Taylor, L., Jr.↗
NASA NTRS1981

Contextual classification of multispectral image data - An unbiased estimator for the context distribution

Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach. This statistical classification algorithm exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context distribution. Here a discussion is given of an unbiased estimator of the context distribution which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗
NASA NTRS1982

Evaluation of small area crop estimation techniques using LANDSAT- and ground-derived data

Studies completed in fiscal year 1981 in support of the clustering/classification and preprocessing activities of the Domestic Crops and Land Cover project. The theme throughout the study was the improvement of subanalysis district (usually county level) crop hectarage estimates, as reflected in the following three objectives: (1) to evaluate the current U.S. Department of Agriculture Statistical Reporting Service regression approach to crop area estimation as applied to the problem of obtaining subanalysis district estimates; (2) to develop and test alternative approaches to subanalysis district estimation; and (3) to develop and test preprocessing techniques for use in improving subanalysis district estimates.

Amis, M. L.↗
NASA NTRS1981

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗
NASA NTRS1983

On the error in crop acreage estimation using satellite (LANDSAT) data

The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

Chhikara, R.↗
NASA NTRS1982

A comparison of minimum distance and maximum likelihood techniques for proportion estimation

The estimation of mixing proportions P sub 1, P sub 2,...P sub m in the mixture density f(x) = the sum of the series P sub i F sub i(X) with i = 1 to M is often encountered in agricultural remote sensing problems in which case the p sub i's usually represent crop proportions. In these remote sensing applications, component densities f sub i(x) have typically been assumed to be normally distributed, and parameter estimation has been accomplished using maximum likelihood (ML) techniques. Minimum distance (MD) estimation is examined as an alternative to ML where, in this investigation, both procedures are based upon normal components. Results indicate that ML techniques are superior to MD when component distributions actually are normal, while MD estimation provides better estimates than ML under symmetric departures from normality. When component distributions are not symmetric, however, it is seen that neither of these normal based techniques provides satisfactory results.

Woodward, W. A.↗
NASA NTRS1983

State and model error estimation for elliptic systems: Applications to large antenna static shape determination

This paper outlines the application of various estimation approaches to the problem of static shape determination for large antenna systems. The problem consists of estimating the shape of an antenna surface from measurements of its static deflection. The estimation schemes are based on any one of the modeling options of a single PDE for early insight and understanding, coarse-resolution multiple-PDE models for parametric studies and fine-resolution piecewise-continuum models for detailed design. For any one of these three models, estimator design can be developed using an infinite-dimensional approach, where the necessary finite-element truncation and approximation is conducted after the analytical design has taken place, or it can be based on a finite-dimensional approach, where the model is truncated before the estimation problem is formulated. One of the main objectives of the paper is to develop both approaches while simultaneously investigating their differences and similarities. Simulation results of an application of the finite-dimensional approach to a large parabolic reflector are presented.

Rodriguez, G.↗
NASA NTRS1982

Estimation of context for statistical classification of multispectral image data

Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach. This statistical classification algorithm exploits the tendency of certain ground cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context function. An unbiased estimator of the context function is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context-function estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context-function estimation techniques.

Tilton, J. C.↗
NASA NTRS1981

A function space approach to smoothing with applications to model error estimation for flexible spacecraft control

A function space approach to smoothing is used to obtain a set of model error estimates inherent in a reduced-order model. By establishing knowledge of inevitable deficiencies in the truncated model, the error estimates provide a foundation for updating the model and thereby improving system performance. The function space smoothing solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for spacecraft attitude control.

Rodriguez, G.↗
NASA NTRS1982

A new solution to parameter adaptive estimation of random processes

This paper is concerned with the development of an adaptive state estimator that is capable of tracking switched linear plants that undergo rapid configuration changes. The particular adaptive estimator developed here is called the Sliding Window Detector/Estimator (SWDE) algorithm. Unlike previous algorithms, the SWDE algorithm is designed specifically for the switched-linear plant problem. It uses a joint detection/estimation approach to give a very close approximation to the unrealizable optimum switched-linear estimator. An extremely reliable and accurate estimator can be constructed by combining a modified Parameter Adaptive Estimation (PAE) algorithm with SWDE. The algorithm has been fully verified by extensive computer simulation, and the implementation advantages afforded by this method make it suitable for use in a wide variety of applications.

Zwicke, P. E.↗
NASA NTRS1984

An approach to software cost estimation

A general procedure for software cost estimation in any environment is outlined. The basic concepts of work and effort estimation are explained, some popular resource estimation models are reviewed, and the accuracy of source estimates is discussed. A software cost prediction procedure based on the experiences of the Software Engineering Laboratory in the flight dynamics area and incorporating management expertise, cost models, and historical data is described. The sources of information and relevant parameters available during each phase of the software life cycle are identified. The methodology suggested incorporates these elements into a customized management tool for software cost prediction. Detailed guidelines for estimation in the flight dynamics environment developed using this methodology are presented.

Mcgarry, F.↗
NASA NTRS1983

Model error estimation for distributed systems described by elliptic equations

A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.

Rodriguez, G.↗
NASA NTRS1984

Center of mass estimation in closed vortices - A verification in principle and practice

The problem of tracking closed mesoscale vortices using center of mass estimation techniques is studied. Three estimators are evaluated using data from a warm core Gulf Stream ring. The comparisons show that a method based on the intersection of perpendicular bisectors and one using a least-squares fit of a conic section perform comparably. The perpendicular bisector algorithm is used in conjunction with a Gaussian ring model and a star-shaped survey pattern to produce an expected error curve as a function of vortex translation, survey speed and vortex size. For typical ring parameters, center estimation is usually possible to within + or - 5 km. The feasibility of using differing data sets to construct a history of ring motion based on a coordinate system moving with the ring is also investigated. In this way, the validity of using satellite-derived data and drifter trajectories to estimate the center of mass of a mesoscale feature is assessed. The results of the analysis demonstrate that the location of the deeper structure of the ring and the surface expression are sufficiently well correlated to permit dynamically relevant calculations based on surface measurements. It is shown that satellite-derived data can be used to approximate the center of mass trajectory to within the error in the individual center estimates for the period analyzed. The Lagrangian-drifter-derived centers are offset from the center of mass trajectory in a manner consistent with kinematic arguments.

Hooker, S. B.↗
NASA NTRS1985

Estimating the R-curve from residual strength data

A method is presented for estimating the crack-extension resistance curve (R-curve) from residual-strength (maximum load against original crack length) data for precracked fracture specimens. The method allows additional information to be inferred from simple test results, and that information can be used to estimate the failure loads of more complicated structures of the same material and thickness. The fundamentals of the R-curve concept are reviewed first. Then the analytical basis for the estimation method is presented. The estimation method has been verified in two ways. Data from the literature (involving several materials and different types of specimens) are used to show that the estimated R-curve is in good agreement with the measured R-curve. A recent predictive blind round-robin program offers a more crucial test. When the actual failure loads are disclosed, the predictions are found to be in good agreement.

Orange, T. W.↗