Search NASA⌕ Search

SEARCH · Search NASA

Results for “Iterative reconstruction”

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.

At least 55 records · Page 3

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗

Reconstruction of coded aperture images

Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

Bielefeld, Michael J.↗

Algorithms For Segmentation Of Complex-Amplitude SAR Data

Several algorithms implement improved method of segmenting highly speckled, high-resolution, complex-amplitude synthetic-aperture-radar (SAR) digitized images into regions, within each backscattering characteristics similar or homogeneous from place to place. Method provides for approximate, deterministic solution by two alternative algorithms almost always converging to local minimums: one, Iterative Conditional Modes (ICM) algorithm, which locally maximizes posterior probability density of region labels; other, Maximum Posterior Marginal (MPM) algorithm, which maximizes posterior marginal density of region labels at each pixel location. ICM algorithm optimizes reconstruction of underlying scene. MPM algorithm minimizes expected number of misclassified pixels, possibly better in remote sensing of natural scenes.

Rignot, Eric J. M.↗

Simulation of a Periodic Jet in a Crossflow with a RANS Solver Using an Unstructured Grid

A second-order unstructured-grid code, developed and used primarily for steady aerodynamic simulations, is applied to the synthetic jet in a cross flow. The code, FUN3D, is a vertex-centered finite-volume method originally developed by Anderson[1, 2], and is currently supported by members of the Fast Adaptive Aerospace Tools team at NASA Langley. Used primarily for design[3] and analysis[4] of steady aerodynamic configurations, FUN3D incorporates a discrete adjoint capability, and supports parallel computations using MPI. A detailed description of the FUN3D code can be found in the references given above. The code is under continuous development and contains a variety of flux splitting algorithms for the inviscid terms, two methods for computing gradients, several turbulence models, and several solution methodologies; all in varying states of development. Only the most robust and reliable components, based on experiences with steady aerodynamic simulations, were employed in this work. As applied in this work, FUN3D solves the Reynolds averaged Navier-Stokes equations using the one equation turbulence model of Spalart and Allmaras[5]. The spatial discretization is formed on unstructured meshes using a vertex-centered approach. The inviscid terms are evaluated by a flux-difference splitting formulation using least-squares reconstruction and Roe-type approximate Riemann fluxes. Green-Gauss gradient evaluations are used for viscous and turbulence modeling terms. The discrete spatial operator is combined with a backward time operator which is then solved iteratively using point or line Gauss-Seidel and local time stepping in a pseudo time. For steady flows, the physical time step is set to infinity and the pseudo time step is ramped up with the iteration count. A second-order backward in time operator is used for time accurate flows with 20 to 50 steps in the pseudo time applied at each physical time step. For this effort, FUN3D was modified to support spatially varying boundary and initial conditions, and unsteady boundary conditions. Also, a specialized in/out flow boundary condition was implemented to model the action of the diaphragm. This boundary condition is described below in more detail. The grids were generated using the internally developed codes GridEX[6] for meshing the surfaces and inviscid regions of the domain, and for CAD access; and MesherX[7] for meshing the viscous regions. Grid spacing in on the surfaces and in the inviscid regions are indirectly controlled by specifying sources. The viscous layers are generated using an advancing layer technique. MeshersX allows the user to control the spatial variation of the first step off the surface, growth rates, and the termination criterion by providing small problem dependent subroutines.

Atkins, H. L.↗

Bayesian Vision for Shape Recovery

We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.

Jalobeanu, Andre↗

Method and apparatus for sensor fusion

Method and apparatus for fusion of data from optical and radar sensors by error minimization procedure is presented. The method was applied to the problem of shape reconstruction of an unknown surface at a distance. The method involves deriving an incomplete surface model from an optical sensor. The unknown characteristics of the surface are represented by some parameter. The correct value of the parameter is computed by iteratively generating theoretical predictions of the radar cross sections (RCS) of the surface, comparing the predicted and the observed values for the RCS, and improving the surface model from results of the comparison. Theoretical RCS may be computed from the surface model in several ways. One RCS prediction technique is the method of moments. The method of moments can be applied to an unknown surface only if some shape information is available from an independent source. The optical image provides the independent information.

Krishen, Kumar↗

Improving the geological interpretation of magnetic and gravity satellite anomalies

Quantitative analysis of the geologic component of observed satellite magnetic and gravity fields requires accurate isolation of the geologic component of the observations, theoretically sound and viable inversion techniques, and integration of collateral, constraining geologic and geophysical data. A number of significant contributions were made which make quantitative analysis more accurate. These include procedures for: screening and processing orbital data for lithospheric signals based on signal repeatability and wavelength analysis; producing accurate gridded anomaly values at constant elevations from the orbital data by three-dimensional least squares collocation; increasing the stability of equivalent point source inversion and criteria for the selection of the optimum damping parameter; enhancing inversion techniques through an iterative procedure based on the superposition theorem of potential fields; and modeling efficiently regional-scale lithospheric sources of satellite magnetic anomalies. In addition, these techniques were utilized to investigate regional anomaly sources of North and South America and India and to provide constraints to continental reconstruction. Since the inception of this research study, eleven papers were presented with associated published abstracts, three theses were completed, four papers were published or accepted for publication, and an additional manuscript was submitted for publication.

Hinze, William J.↗

Imaging Asteroid 4 Vesta Using the Framing Camera

The Framing Camera (FC) onboard the Dawn spacecraft serves a dual purpose. Next to its central role as a prime science instrument it is also used for the complex navigation of the ion drive spacecraft. The CCD detector with 1024 by 1024 pixels provides the stability for a multiyear mission and its high requirements of photometric accuracy over the wavelength band from 400 to 1000 nm covered by 7 band-pass filters. Vesta will be observed from 3 orbit stages with image scales of 227, 63, and 17 m/px, respectively. The mapping of Vesta s surface with medium resolution will be only completed during the exit phase when the north pole will be illuminated. A detailed pointing strategy will cover the surface at least twice at similar phase angles to provide stereo views for reconstruction of the topography. During approach the phase function of Vesta was determined over a range of angles not accessible from earth. This is the first step in deriving the photometric function of the surface. Combining the topography based on stereo tie points with the photometry in an iterative procedure will disclose details of the surface morphology at considerably smaller scales than the pixel scale. The 7 color filters are well positioned to provide information on the spectral slope in the visible, the depth of the strong pyroxene absorption band, and their variability over the surface. Cross calibration with the VIR spectrometer that extends into the near IR will provide detailed maps of Vesta s surface mineralogy and physical properties. Georeferencing all these observation will result in a coherent and unique data set. During Dawn s approach and capture FC has already demonstrated its performance. The strong variation observed by the Hubble Space Telescope can now be correlated with surface units and features. We will report on results obtained from images taken during survey mode covering the whole illuminated surface. Vesta is a planet-like differentiated body, but its surface gravity and escape velocity are comparable to those of other asteroids and hence much smaller than those of the inner planets or

Keller, H. Uwe↗

Computer tomography of flows external to test models

Computer tomographic techniques for reconstruction of three-dimensional aerodynamic density fields, from interferograms recorded from several different viewing directions were studied. Emphasis is on the case in which an opaque object such as a test model in a wind tunnel obscures significant regions of the interferograms (projection data). A method called the Iterative Convolution Method (ICM), existing methods in which the field is represented by a series expansions, and analysis of real experimental data in the form of aerodynamic interferograms are discussed.

Prikryl, I.↗

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗

Phase retrieval for the Hubble Space Telescope using iterative propagation algorithms

Phase retrieval algorithms, including the iterative transform algorithm and gradient search algorithms, were generalized to include the effects of propagation through a complicated optical system and to discount the effects of bad CCD pixels. For the gradient search algorithms, analytic gradients were derived that greatly speed up the computation over finite difference methods. For the Hubble Space Telescope (HST), the aperture function was reconstructed and the phase errors were retrieved. This information is useful to design correction optics for the telescope and for the deconvolution of blurred images from the HST.

Fienup, J. R.↗

Development of a Twin-spool Turbofan Engine Simulation Using the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3 of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

thermodynamic simulation↗

Development of a Twin-Spool Turbofan Engine Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3% of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

numerical simulation↗

Stochastic Reconstruction of Thermal Protection Material Properties from Arc-Jet Experiments

Material response models are used to assess reliability using variances in the bond-line temperature predictions based on uncertainties in trajectory, aerothermal environment, and material properties. A key deficiency in the current approach is that input uncertainties are too often subjective, empirical, or ad-hoc, and are not rigorously linked to the arc-jet test data used to develop the TPS material model. While materials such as PICA are well understood, future missions may require more novel materials such as HEEET where unknown uncertainties have real consequences on the ability to assess reliability. A quantifiable estimate of reliability requires an iterative methodology where the parameters driving the variance in bond-line temperature (for example) are systematically identified. A test campaign to collect data or develop new models can then be identified to reduce those input uncertainties. A Bayesian inference loop defines these connections mathematically, i.e., prior knowledge about uncertainty is updated based on observation. While these concepts are well known (and often applied intuitively in a non-rigorous approach), only recent advances in reduced-order modelling have made them computationally viable methods for engineering. By replacing deterministic inverse methods with stochastic approaches, the hope is new materials proposed for future missions can more rapidly be developed with a greater understanding of the TPS material reliability. Two additional steps for the analysis of arc jet test data are discussed. The first is ability to construct a reduced-order model using material response simulations (Icarus/US3D) of the arc-jet test articles, and the second is the inclusion of this surrogate model in the Bayesian inversion process. Both capabilities will be demonstrated using prior PICA arc-jet test data. The quality of a surrogate model will be investigated and the variances on the calibrated material properties will be compared to our current understanding of the PICA material model.

Material response↗

Developing the Future of Gamma-ray Astrophysics with Monolithic Silicon Pixels

This paper explores the potential of AstroPix, a project to develop Complementary Metal Oxide Semiconductor (CMOS) pixels for the next generation of space-based high-energy astrophysics experiments. Multimessenger astrophysics is a rapidly developing field whose upcoming missions need support from new detector technology such as AstroPix. ATLASPix, a monolithic silicon detector optimized for the ATLAS particle detector at CERN, is the beginning of the larger AstroPix project. Energy resolution is a driving parameter in the reconstruction of gamma-ray events, and therefore the characterization of ATLASPix energy resolution is the focus of this paper. The intrinsic energy resolution of the detector exceeded our baseline requirements of 10% at 60 keV. The digital output of ATLASPix results in energy resolutions insufficient to advance gamma-ray astronomy. However, the results from the intrinsic energy resolution indicate the digital capability of the detector can be redesigned, and the next generation of pixels for the larger AstroPix project have already been constructed. Iterations of AstroPix-type pixels are an exciting new technology candidate to support new space-based missions.

Isabella Brewer↗

Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absorption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

Alfano, Robert R.↗

Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

Alfano, Robert R.↗

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗