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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 307 records · Page 17

A new computer approach to map mixed forest features and postprocess multispectral data

A computer technique for mapping mixed softwood and hardwood stands in multispectral satellite imagery of forest regions is described. The purpose of the technique is to obtain smoother resource maps useful in timber harvesting operations. The computer program relies on an algorithm which assesses the size and similarity of adjacent sections on satellite imagery (Landsat-1 data is used) and constructs, through an iteration of the basic algorithm, a more general map of timber mixtures, eliminating the mottled appearance of the raw imagery. Despite difficulties in the experimental analysis of a Texas forest, apparently due to relatively low resolution of the Landsat data, the computer classification approach outlined is suggested as a generally applicable method of creating serviceable maps from multispectral imagery.

Kan, E. P.↗

A hardware implementation of a relaxation algorithm to segment images

Relaxation labelling is a mathematical technique frequently applied in image processing algorithms. In particular, it is extensively used for the purpose of segmenting images. The paper presents a hardware implementation of a segmentation algorithm, for images consisting of two regions, based on relaxation labelling. The algorithm determines, for each pixel, the probability that it should be labelled as belonging to a particular region, for all regions in the image. The label probabilities (labellings) of every pixel are iteratively updated, based on those of the pixel's neighbors, until they converge. The pixel is then assigned to the region correspondent to the maximum label probability. The system consists of a control unit and of a pipeline of segmentation stages. Each segmentation stage emulates in the hardware an iteration of the relaxation algorithm. The design of the segmentation stage is based on commercially available digital signal processing integrated circuits. Multiple iterations are accomplished by stringing stages together or by looping the output of a stage, or string of stages, to its input. The system interfaces with a generic host computer. Given the modularity of the architecture, performance can be enhanced by merely adding segmentation stages.

Loda, Antonio G.↗

Attitude determination and parameter estimation using vector observations - Application

This paper presents tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and earth-pointing attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. In the majority of tests performed, the two methods converge to the same estimates in the same number of iterations, but the new algorithm requires about 60 percent more computational effort. Some cases were found in which the new method converges in fewer iterations than the differential correction, and some for which the differential correction requires fewer iterations.

Markley, F. Landis↗

Advanced development of the boundary element method for elastic and inelastic thermal stress analysis

The focus of this dissertation is on advanced development of the boundary element method for elastic and inelastic thermal stress analysis. New formulations for the treatment of body forces and nonlinear effects are derived. These formulations, which are based on particular integral theory, eliminate the need for volume integrals or extra surface integrals to account for these effects. The formulations are presented for axisymmetric, two and three dimensional analysis. Also in this dissertation, two dimensional and axisymmetric formulations for elastic and inelastic, inhomogeneous stress analysis are introduced. The derivatives account for inhomogeneities due to spatially dependent material parameters, and thermally induced inhomogeneities. The nonlinear formulation of the present work are based on an incremental initial stress approach. Two inelastic solutions algorithms are implemented: an iterative; and a variable stiffness type approach. The Von Mises yield criterion with variable hardening and the associated flow rules are adopted in these algorithms. All formulations are implemented in a general purpose, multi-region computer code with the capability of local definition of boundary conditions. Quadratic, isoparametric shape functions are used to model the geometry and field variables of the boundary (and domain) of the problem. The multi-region implementation permits a body to be modeled in substructured parts, thus dramatically reducing the cost of analysis. Furthermore, it allows a body consisting of regions of different (homogeneous) material to be studied. To test the program, results obtained for simple test cases are checked against their analytic solutions. Thereafter, a range of problems of practical interest are analyzed. In addition to displacement and traction loads, problems with body forces due to self-weight, centrifugal, and thermal loads are considered.

Henry, Donald P., Jr.↗

Photometric properties of lunar terrains derived from Hapke's equation

Hapke's bidirectional reflectance equations provide the most rigorous available description of photometric behavior in terms of physically meaningful parameters. The primary objective of this study was to derive Hapke parameters for the lunar surface from both disk-integrated and disk-resolved photometric data. Hapke's equation was fit to the disk-integrated phase curves and disk-resolved data for dark, average, and bright terrain classes using an iterative, nonlinear least squares algorithm described by Helfenstein. Parameters were initially determined from the disk-integrated data, and the result was applied as a first guess to the iterative solution of parameters for individual terrain classes. Plots are presented of the disk-resolved data normalized to corresponding brightnesses predicted from the disk-integrated solution under the same illumination and viewing geometries. Systematic trends in disk-resolved parameters can be identified. Values for single scattering albedo (w) of the dominantly anorthositic average and bright terrains are significantly larger than the value for the basaltic dark terrains (mare). Values for surge brightness parameters, particle phase function, and average topographic slope angle are also discussed.

Helfenstein, Paul↗

A review of nonstatistical techniques for the estimation of vertical atmospheric structure from remote infrared measurements

Mathematical techniques used in atmospheric profile inversion are reviewed, with the discussion limited to methods that do not require extensive information on the statistical properties of the profiles. The basic problem of the calculation of vertical profiles from noise contaminated infrared spectral measurements is examined. Three specific examples of methods of solution are given: the iterative minimum estimation method, a second linear iterative method, and the algorithm of Chahine. Satellite data are used in an empirical comparison of the methods. Several factors are considered, including the stability of solutions, convergence behavior of the iterative methods, and dependence of the solutions on the first guess, a factor that is particularly important in the treatment of data from other planets.

Conrath, B. J.↗

A Universal Tare Load Prediction Algorithm for Strain-Gage Balance Calibration Data Analysis

An algorithm is discussed that may be used to estimate tare loads of wind tunnel strain-gage balance calibration data. The algorithm was originally developed by R. Galway of IAR/NRC Canada and has been described in the literature for the iterative analysis technique. Basic ideas of Galway's algorithm, however, are universally applicable and work for both the iterative and the non-iterative analysis technique. A recent modification of Galway's algorithm is presented that improves the convergence behavior of the tare load prediction process if it is used in combination with the non-iterative analysis technique. The modified algorithm allows an analyst to use an alternate method for the calculation of intermediate non-linear tare load estimates whenever Galway's original approach does not lead to a convergence of the tare load iterations. It is also shown in detail how Galway's algorithm may be applied to the non-iterative analysis technique. Hand load data from the calibration of a six-component force balance is used to illustrate the application of the original and modified tare load prediction method. During the analysis of the data both the iterative and the non-iterative analysis technique were applied. Overall, predicted tare loads for combinations of the two tare load prediction methods and the two balance data analysis techniques showed excellent agreement as long as the tare load iterations converged. The modified algorithm, however, appears to have an advantage over the original algorithm when absolute voltage measurements of gage outputs are processed using the non-iterative analysis technique. In these situations only the modified algorithm converged because it uses an exact solution of the intermediate non-linear tare load estimate for the tare load iteration.

balance calibration analysis↗

Next-Generation Aura/OMI NO2 and SO2 Products

The measurement of both SO2 and NO2 gases are recognized as an essential component of atmospheric composition missions. We describe current capabilities and limitations of the operational Aura/OMI NO2 and SO2 data that have been used by a large number of researchers. Analyses of the data and validation studies have brought to light a number of areas in which these products can be expanded and improved. Major improvements for new NASA standard (SP) NO2 product include more accurate tropospheric and stratospheric column amounts, along with much improved error estimates and diagnostics. Our approach uses a monthly NO2 climatology based on the NASA Global Modeling Initiative (GMI) chemistry-transport model and takes advantage of OMI data from cloudy scenes to find clean areas where the contribution from the trap NO2 column is relatively small. We then use a new filtering, interpolation and smoothing techniques for separating the stratospheric and tropospheric components of NO2, minimizing the influence of a priori information. The new algorithm greatly improves the structure of stratospheric features relative to the original SP. For the next-generation OMI SO2 product we plan to implement operationally the offline iterative spectral fitting (ISF) algorithm and re-process the OMI Level-2 SO2 dataset using a priori SO2 and aerosol profiles, clouds, and surface reflectivity appropriate for observation conditions. This will improve the ability to detect and quantify weak tropospheric SO2 loadings. The new algorithm is validated using aircraft in-situ data during field campaigns in China (2005 and 2008) and in Maryland (Frostburg, 2010 and DISCOVER-AQ in July 2011). The height of the SO2 plumes will also be estimated for high SO2 loading cases (e.g., volcanic eruptions). The same SO2 algorithm will be applied to the data from OMPS sensor to be launched on NPP satellite later this year. The next-generation NO2 and SO2 products will provide critical information (e.g., averaging kernels) for evaluation of chemistry-transport models, for data assimilation, and to impose top-down constraints on the SO2 and NO2 emission sources.

Krotkov, Nickolay↗

Linear pose estimation from points or lines

We present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. We present a number of simulations which compare our results to two other recent linear algorithm as well as to iterative approaches.

pose estimation algorithms↗

Advanced applications of BEM to inelastic analysis of solids

Newly evolved boundary element solution algorithms are utilized for solving a range of elastoplastic and thermoplastic problems. The first algorithm is the typical iterative procedure in which the unknown boundary solution and the initial stress (or strain) rates are found together in an incremental iterative fashion. The second one is a variable stiffness type approach in which the incremental boundary solution is obtained in a direct (noniterative) manner. The third procedure differs from the two prior algorithms in that volume integration is not needed to incorporate the nonlinear effects in the analysis. Instead, initial stress rates are introduced in the boundary element system by way of particular integrals. The methodology is used in a general purpose, multiregion system that employs quadratic isoparametric shape functions to model the geometry and field variables of the body and can admit up to 15 substructured areas of different material properties.

Banerjee, P. K.↗

Flight test evaluation of a digital controller used in a VTOL automatic approach and landing system

As part of the NASA Langley Research Center's effort to develop technology for VTOL operation in the air transportation system in the late 1980's and beyond, research has been conducted aimed at developing digital controller design procedures. This paper describes the verification of one design procedure by the flight evaluation of an advanced digital control algorithm. The control algorithm, operating at 10 iterations per second, follows step guidance commands with zero steady state error and thus provides an autotrim capability for the nonlinear vehicle. Changes in vehicle dynamics are accounted for using a gain scheduling technique. This control algorithm is combined with sensor filters, a trajectory generator, and a closed loop guidance algorithm to form a VTOL autoland system. A CH-47 tandem rotor helicopter which contains a set of sensors, onboard digital flight computers and electro-hydraulic actuators is used in the evaluation. All software, except input-output routines, is coded in FORTRAN using floating point arithmetic and executed in the flight computer. This autoland system is exercised by automatically flying straight-in descending decelerating trajectories typical of VFR manual approaches to a predetermined landing pad.

Downing, D. R.↗

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

Tarabalka, Yuliya↗

Fast polar decomposition of an arbitrary matrix

The polar decomposition of an m x n matrix A of full rank, where m is greater than or equal to n, can be computed using a quadratically convergent algorithm. The algorithm is based on a Newton iteration involving a matrix inverse. With the use of a preliminary complete orthogonal decomposition the algorithm can be extended to arbitrary A. How to use the algorithm to compute the positive semi-definite square root of a Hermitian positive semi-definite matrix is described. A hybrid algorithm which adaptively switches from the matrix inversion based iteration to a matrix multiplication based iteration due to Kovarik, and to Bjorck and Bowie is formulated. The decision when to switch is made using a condition estimator. This matrix multiplication rich algorithm is shown to be more efficient on machines for which matrix multiplication can be executed 1.5 times faster than matrix inversion.

Higham, Nicholas J.↗

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

wave-front sensing and control↗

Numerical optimization in Hilbert space using inexact function and gradient evaluations

Trust region algorithms provide a robust iterative technique for solving non-convex unstrained optimization problems, but in many instances it is prohibitively expensive to compute high accuracy function and gradient values for the method. Of particular interest are inverse and parameter estimation problems, since function and gradient evaluations involve numerically solving large systems of differential equations. A global convergence theory is presented for trust region algorithms in which neither function nor gradient values are known exactly. The theory is formulated in a Hilbert space setting so that it can be applied to variational problems as well as the finite dimensional problems normally seen in trust region literature. The conditions concerning allowable error are remarkably relaxed: relative errors in the gradient error condition is automatically satisfied if the error is orthogonal to the gradient approximation. A technique for estimating gradient error and improving the approximation is also presented.

Carter, Richard G.↗