SEARCH · Engineering Papers
Results for “covariates”
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.
Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems
Explore the source record for details and available documents.
Evaluating Lunar Descent and Landing Performance From a Near Rectilinear Halo Orbit Using Linear Covariance Resetting Techniques
Upcoming lunar programs are striving the achieve precision landing in a safe and robust manner. Various elements impact this mission objective ranging from on-orbit operations with ground station tracking to incorporating relative sensors with hazard detection and avoidance (HDA) to support the final approach and landing phase. Modeling the impacts of ground tracking, trajectory replanning, relative navigation sensors, and particularly a potential HDA system on the integrated closed-loop GN\&C system performance poses a unique challenge due to the complexity and interaction with multiple facets of the vehicle including the trajectory design, sensing hardware, navigation system, guidance and targeting, and the overall mission concept of operations. This paper outlines techniques to systematically analyze and compare the performance impacts of ground tracking and replanning and an HDA system where the onboard navigation errors are reset or uploaded from an external source and the vehicle's reference trajectory is regenerated requiring the system dispersions to also be reset to reflect this in-flight profile adjustment. To illustrate the application of these general techniques for analyzing the performance impacts due to incorporating these resetting events, they are demonstrated with a human lunar descent and landing scenario starting from a near rectilinear halo orbit (NRHO) until the vehicle precisely reaches its predetermined landing site on the lunar surface. Performance metrics such as inertial and relative navigation errors, trajectory dispersions, footprint dispersions, and propellant usage are provided.
Soil moisture background error covariance and data assimilation in a coupled land‐atmosphere model
Explore the source record for details and available documents.
A Method for Estimating and Partitioning the Covariance of Wind Speed Observation Error from GNSS Reflectometry
Explore the source record for details and available documents.
Estimation of the mean of a discrete parameter, covariance stationary, stochastic process in rotation sampling
Constrained optimization procedure for deriving linear estimator of population mean in rotation sampling
Use of the three-dimensional covariance matrix in analyzing the polarization properties of plane waves.
Explore the source record for details and available documents.
An Expression for the Transformed Covariance Matrix of Multivariate Normal Populations
The problem is considered of classifying into one of m distinct n-variate classes an arbitrary n-channel multispectral measurement vector x. The classification procedure used is the maximum likelihood procedure. Information loss in compressing the n-channel data to k channels is taken to be the difference in the average interclass divergences (or probability of misclassification) in n-space and in k-space. Data compression is accomplished by kxn linear transformation i.e., multiplication of the spectral n-vector by a kxn matrix of rank k.
A conservative bound on the estimation error covariance matrix in the presence of correlated driving noise and correlated discrete measurement noise.
Explore the source record for details and available documents.
Scale-covariant theory of gravitation and astrophysical applications
Generalized Einstein equations invariant under scale transformations are presented, and several astrophysical tests studied. It is assumed that the dynamics of atoms or clocks used as measuring apparatus is given a priori. Connection with gauge fields and broken symmetries is made through the cosmological constant.
Scale covariant cosmology and the temperature of the earth
Geological data are used as cosmological determinants in a study of the temperature of the early earth (2.3 to 4.5 billion years ago). It is known that the energy output of the sun during that period was on the order of 30-40% lower than at present, and deduced that the mean temperature of the earth should have fallen to as low as 245 K, i.e., below the freezing point of seawater. Strong evidence exists, however, to indicate that algae (therefore liquid water) was present. To reconcile the discrepancies, a model is proposed whereby terrestrial G and M vary. It is further noted that atmosphere H2 may be a better agent than NH3 for producing a greenhouse effect.
The 3 K blackbody radiation, Dirac's Large Numbers Hypothesis, and scale-covariant cosmology
A program is described which is intended to derive a generalized system of gravitational equations that allow (but do not require) G to vary, to use the 3-K blackbody radiation to fix the relation between G and the gauge function, and to employ Dirac's (1937) Large Numbers Hypothesis to derive the geometry of the universe. Einstein's equations are retained in their total integrity, but the specification is made that they are valid only when gravitational units are used. A scale-invariant form of Einstein's equations is obtained, and from this are derived the energy conservation law, the baryon-number conservation law, and the appropriate cosmological equations. Dirac's proposals of 1937 and 1973 are incorporated into the formalism, and a gauge based on consolidation of the 3-K blackbody radiation is presented. A unique solution for the geometry of the universe is determined for zero curvature solely from the 3-K radiation and the Large Numbers Hypothesis; this solution predicts a deceleration parameter exactly equal to unity.
Sample-moment estimates for the mean vector and the covariance matrix for a sample of incomplete data vectors
There are no author-identified significant results in this report.
A discriminant approach to parameter estimation in the linear model with unknown variance-covariance matrix
There are no author-identified significant results in this report.
Covariance analyses of satellite-derived mesoscale wind fields
Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.
Covariance analysis of the airborne laser ranging system
The requirements and limitations of employing an airborne laser ranging system for detecting crustal shifts of the Earth within centimeters over a region of approximately 200 by 400 km are presented. The system consists of an aircraft which flies over a grid of ground deployed retroreflectors, making six passes over the grid at two different altitudes. The retroreflector baseline errors are assumed to result from measurement noise, a priori errors on the aircraft and retroreflector positions, tropospheric refraction, and sensor biases.
Brazil wheat yield covariance model
A model based on multiple regression was developed to estimate wheat yields for the wheat growing states of Rio Grande do Sul, Parana, and Santa Catarina in Brazil. The meteorological data of these three states were pooled and the years 1972 to 1979 were used to develop the model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature.
Brazil soybean yield covariance model
A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.