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At least 289 records · Page 16

SSC Geopositional Assessment of an AWiFS Image Orthorectified Product

The geopositional accuracy of an AWiFS (Advanced Wide Field Sensor) orthorectified product was evaluated. Specifically, the image products were acquired by the Indian Remote Sensing Resourcesat-1 satellite, then orthorectified by GeoEye . Analysis was performed using DOQs (digital orthophoto quadrangles) and other reference sources of similar accuracy. A total of six AWiFS images were characterized. These images were acquired over the continental United States from June through September 2005. The images were equally divided between the two AWiFS cameras. Forty to fifty check points were collected manually per scene and analyzed to determine overall circular error, estimates of horizontal bias, and other systematic errors.

Kenton, Ross↗

Verification of Anisotropic Mesh Adaptation for Turbulent Simulations over ONERA M6 Wing

Unstructured anisotropic mesh adaptation is known to be an efficient way to control discretization errors in Computational Fluid Dynamics (CFD) simulations. Method verification is required to provide the confidence for routine use in production analysis. The current work aims at verification of anisotropic mesh adaptation for RANS simulations over the ONERA M6 wing. The present verification study is performed using four different flow solvers, three different implementations of the metric field, and three mesh mechanics packages. Two of the flow solvers use stabilized finite-element discretizations (FUN3D-SFE and GGNS), one uses finite-volume discretization (FUN3D-FV), and the last one uses mixed finite-volume and finite element discretizations (Wolf). The mesh adaptation is based on an error estimator that aims to control the quadratic error term in the linear interpolation of Mach number. Two sets of adaptations were performed; the first one controls the interpolation error in L2 norm and the second one controls the interpolation error in L4 norm. Convergence studies were performed on the forces and the pitching moment using all four solvers, and the results are compared with previously verified convergence studies on fixed (nonadapted) meshes. Both forces and pitching moment on adapted meshes are found to be converging to the fine mesh values faster than those on fixed meshes. In addition to forces and moments, convergence of surface pressure and skin friction coefficients at various measurement locations on the wing are also presented. Adapted-mesh surface pressure distributions agree with the fine fixed mesh pressure distributions. Adapted-mesh skin friction distributions contain high frequency noise with mean values approaching the fixed mesh pressure skin friction distributions.

Aravind Balan↗

Bounding filter - A simple solution to lack of exact a priori statistics.

Wiener and Kalman-Bucy estimation problems assume that models describing the signal and noise stochastic processes are exactly known. When this modeling information, i.e., the signal and noise spectral densities for Wiener filter and the signal and noise dynamic system and disturbing noise representations for Kalman-Bucy filtering, is inexactly known, then the filter's performance is suboptimal and may even exhibit apparent divergence. In this paper a system is designed whereby the actual estimation error covariance is bounded by the covariance calculated by the estimator. Therefore, the estimator obtains a bound on the actual error covariance which is not available, and also prevents its apparent divergence.

Nahi, N. E.↗

Low-dimensional Representation of Error Covariance

Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.

Tippett, Michael K.↗

The quality of photometric information in the Hipparcos Input Catalog

Comparison with independent photoelectric photometry is used to assess the quality of magnitudes and colors in the Hipparcos Input Catalog. These magnitudes and colors will play an important role in the luminosity calibration of Hipparcos stars. We conclude that photoelectric photometry, available for about 37 percent of the catalog, is of uniformly good quality, and the error estimates in the Catalog are very accurate. On the other hand, colors determined from poor spectral classes suffer from very significant errors, also correctly estimated in the Catalog, which make them essentially unsuited for the purpose of luminosity calibration. Only stars with either photoelectric colors or good 2D spectral classes can be used in a high-accuracy luminosity calibration.

Casertano, Stefano↗

Single-Frequency GPS Relative Navigation in a High Ionosphere Orbital Environment

The Global Positioning System (GPS) provides a convenient source for space vehicle relative navigation measurements, especially for low Earth orbit formation flying and autonomous rendezvous mission concepts. For single-frequency GPS receivers, ionospheric path delay can be a significant error source if not properly mitigated. In particular, ionospheric effects are known to cause significant radial position error bias and add dramatically to relative state estimation error if the onboard navigation software does not force the use of measurements from common or shared GPS space vehicles. Results from GPS navigation simulations are presented for a pair of space vehicles flying in formation and using GPS pseudorange measurements to perform absolute and relative orbit determination. With careful measurement selection techniques relative state estimation accuracy to less than 20 cm with standard GPS pseudorange processing and less than 10 cm with single-differenced pseudorange processing is shown.

Conrad, Patrick R.↗

Large Area Crop Inventory Experiment (LACIE). Phase 1: Evaluation report

It appears that the Large Area Crop Inventory Experiment over the Great Plains, can with a reasonable expectation, be a satisfactory component of a 90/90 production estimator. The area estimator produced more accurate area estimates for the total winter wheat region than for the mixed spring and winter wheat region of the northern Great Plains. The accuracy does appear to degrade somewhat in regions of marginal agriculture where there are small fields and abundant confusion crops. However, it would appear that these regions tend also to be marginal with respect to wheat production and thus increased area estimation errors do not greatly influence the overall production estimation accuracy in the United States. The loss of segments resulting from cloud cover appears to be a random phenomenon that introduces no significant bias into the estimates. This loss does increase the variance of the estimates.

Source record↗

Practical Aspects of Stabilized FEM Discretizations of Nonlinear Conservation Law Systems with Convex Extension

This talk considers simplified finite element discretization techniques for first-order systems of conservation laws equipped with a convex (entropy) extension. Using newly developed techniques in entropy symmetrization theory, simplified forms of the Galerkin least-squares (GLS) and the discontinuous Galerkin (DG) finite element method have been developed and analyzed. The use of symmetrization variables yields numerical schemes which inherit global entropy stability properties of the POE system. Central to the development of the simplified GLS and DG methods is the Degenerative Scaling Theorem which characterizes right symmetrizes of an arbitrary first-order hyperbolic system in terms of scaled eigenvectors of the corresponding flux Jacobean matrices. A constructive proof is provided for the Eigenvalue Scaling Theorem with detailed consideration given to the Euler, Navier-Stokes, and magnetohydrodynamic (MHD) equations. Linear and nonlinear energy stability is proven for the simplified GLS and DG methods. Spatial convergence properties of the simplified GLS and DO methods are numerical evaluated via the computation of Ringleb flow on a sequence of successively refined triangulations. Finally, we consider a posteriori error estimates for the GLS and DG demoralization assuming error functionals related to the integrated lift and drag of a body. Sample calculations in 20 are shown to validate the theory and implementation.

Barth, Timothy↗

Development of an Output-based Adaptive Method for Multi-Dimensional Euler and Navier-Stokes Simulations

The use of computational simulations in the prediction of complex aerodynamic flows is becoming increasingly prevalent in the design process within the aerospace industry. Continuing advancements in both computing technology and algorithmic development are ultimately leading to attempts at simulating ever-larger, more complex problems. However, by increasing the reliance on computational simulations in the design cycle, we must also increase the accuracy of these simulations in order to maintain or improve the reliability arid safety of the resulting aircraft. At the same time, large-scale computational simulations must be made more affordable so that their potential benefits can be fully realized within the design cycle. Thus, a continuing need exists for increasing the accuracy and efficiency of computational algorithms such that computational fluid dynamics can become a viable tool in the design of more reliable, safer aircraft. The objective of this research was the development of an error estimation and grid adaptive strategy for reducing simulation errors in integral outputs (functionals) such as lift or drag from from multi-dimensional Euler and Navier-Stokes simulations. In this final report, we summarize our work during this grant.

Darmofal, David L.↗

Random errors of oceanic monthly rainfall derived from SSM/I using probability distribution functions

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.

Chang, Alfred T. C.↗

Toward Automatic Verification of Goal-Oriented Flow Simulations

We demonstrate the power of adaptive mesh refinement with adjoint-based error estimates in verification of simulations governed by the steady Euler equations. The flow equations are discretized using a finite volume scheme on a Cartesian mesh with cut cells at the wall boundaries. The discretization error in selected simulation outputs is estimated using the method of adjoint-weighted residuals. Practical aspects of the implementation are emphasized, particularly in the formulation of the refinement criterion and the mesh adaptation strategy. Following a thorough code verification example, we demonstrate simulation verification of two- and three-dimensional problems. These involve an airfoil performance database, a pressure signature of a body in supersonic flow and a launch abort with strong jet interactions. The results show reliable estimates and automatic control of discretization error in all simulations at an affordable computational cost. Moreover, the approach remains effective even when theoretical assumptions, e.g., steady-state and solution smoothness, are relaxed.

Simulations↗

Optimization of satellite altimeter and wave height measurements

Two techniques for simultaneously estimating altitude, ocean wave height, and signal-to-noise ratio from the GEOS-C satellite altimeter data are described. One technique was based on maximum likelihood estimation, MLE, and the other on minimum mean square error estimation, MMSE. Performance was determined by comparing the variance and bias of each technique with the variance and bias of the smoothed output from the Geos altimeter tracker. Ocean wave height tracking performance for the MLE and MMSE algorithms was measured by comparing the variance and bias of the wave height estimates with that of the expression for the return waveform obtained by a fit to the average output of the 16 waveform sampling gates.

Dooley, R. P.↗

Some plane curvature approximations

An analytical technique is developed to estimate (with second-order accuracy) the curvature of a sufficiently smooth plane curve defined in finite form. The derivation of the approximations from local information is explained in detail; the continuity and invariance of the estimates under translation and rotation are demonstrated; and examples, error estimates, and a broken-line extension are presented. The suitability of the present technique for computer implementation is indicated.

Mjolsness, R. C.↗

Situation assessment in the Paladin tactical decision generation system

Paladin is a real-time tactical decision generator for air combat engagements. Paladin uses specialized knowledge-based systems and other Artificial Intelligence (AI) programming techniques to address the modern air combat environment and agile aircraft in a clear and concise manner. Paladin is designed to provide insight into both the tactical benefits and the costs of enhanced agility. The system was developed using the Lisp programming language on a specialized AI workstation. Paladin utilizes a set of air combat rules, an active throttle controller, and a situation assessment module that have been implemented as a set of highly specialized knowledge-based systems. The situation assessment module was developed to determine the tactical mode of operation (aggressive, defensive, neutral, evasive, or disengagement) used by Paladin at each decision point in the air combat engagement. Paladin uses the situation assessment module; the situationally dependent modes of operation to more accurately represent the complex decision-making process of human pilots. This allows Paladin to adapt its tactics to the current situation and improves system performance. Discussed here are the details of Paladin's situation assessment and modes of operation. The results of simulation testing showing the error introduced into the situation assessment module due to estimation errors in positional and geometric data for the opponent aircraft are presented. Implementation issues for real-time performance are discussed and several solutions are presented, including Paladin's use of an inference engine designed for real-time execution.

Mcmanus, John W.↗

Procedures to validate/correct calibration error in solar backscattered ultraviolet instruments

The Nimbus 7 SBUV measures the same latitude ozone at widely different sun angle conditions at the ascent and descent part of the orbit during the summer solstice. This situation is used in a particular procedure (Ascent/Descent) to obtain the relative channel-to-channel calibration error for channels 273 nm to 306 nm. These estimated errors are combined with results from the Pair Justification procedure to correct the sun-view diffuser drift in calibration from November 1978 to February 1987 for the shorter wavelength channels that measure upper stratospheric ozone. Some preliminary re-calirated Nimbus 7 SBUV data in 1989 is compared with the first set of SBUV measurements flown on the Space Shuttle.

Taylor, Steven L.↗

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Truong, Son H.↗

Good Practices in Free-energy Calculations

As access to computational resources continues to increase, free-energy calculations have emerged as a powerful tool that can play a predictive role in drug design. Yet, in a number of instances, the reliability of these calculations can be improved significantly if a number of precepts, or good practices are followed. For the most part, the theory upon which these good practices rely has been known for many years, but often overlooked, or simply ignored. In other cases, the theoretical developments are too recent for their potential to be fully grasped and merged into popular platforms for the computation of free-energy differences. The current best practices for carrying out free-energy calculations will be reviewed demonstrating that, at little to no additional cost, free-energy estimates could be markedly improved and bounded by meaningful error estimates. In energy perturbation and nonequilibrium work methods, monitoring the probability distributions that underlie the transformation between the states of interest, performing the calculation bidirectionally, stratifying the reaction pathway and choosing the most appropriate paradigms and algorithms for transforming between states offer significant gains in both accuracy and precision. In thermodynamic integration and probability distribution (histogramming) methods, properly designed adaptive techniques yield nearly uniform sampling of the relevant degrees of freedom and, by doing so, could markedly improve efficiency and accuracy of free energy calculations without incurring any additional computational expense.

Pohorille, Andrew↗

Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).

Ciais, Philippe↗