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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Dispersed Fringe Sensing Analysis - DFSA

Dispersed Fringe Sensing (DFS) is a technique for measuring and phasing segmented telescope mirrors using a dispersed broadband light image. DFS is capable of breaking the monochromatic light ambiguity, measuring absolute piston errors between segments of large segmented primary mirrors to tens of nanometers accuracy over a range of 100 micrometers or more. The DFSA software tool analyzes DFS images to extract DFS encoded segment piston errors, which can be used to measure piston distances between primary mirror segments of ground and space telescopes. This information is necessary to control mirror segments to establish a smooth, continuous primary figure needed to achieve high optical quality. The DFSA tool is versatile, allowing precise piston measurements from a variety of different optical configurations. DFSA technology may be used for measuring wavefront pistons from sub-apertures defined by adjacent segments (such as Keck Telescope), or from separated sub-apertures used for testing large optical systems (such as sub-aperture wavefront testing for large primary mirrors using auto-collimating flats). An experimental demonstration of the coarse-phasing technology with verification of DFSA was performed at the Keck Telescope. DFSA includes image processing, wavelength and source spectral calibration, fringe extraction line determination, dispersed fringe analysis, and wavefront piston sign determination. The code is robust against internal optical system aberrations and against spectral variations of the source. In addition to the DFSA tool, the software package contains a simple but sophisticated MATLAB model to generate dispersed fringe images of optical system configurations in order to quickly estimate the coarse phasing performance given the optical and operational design requirements. Combining MATLAB (a high-level language and interactive environment developed by MathWorks), MACOS (JPL s software package for Modeling and Analysis for Controlled Optical Systems), and DFSA provides a unique optical development, modeling and analysis package to study current and future approaches to coarse phasing controlled segmented optical systems.

Sigrist, Norbert↗
NASA NTRS1979

Estimating crop proportions from remotely sensed data

The classification/pixel-count method for estimating the proportion of wheat in each segment is theoretically biased even if all distributional assumptions are met. Alternative ways to estimate crop proportions are examined and their performance testing is considered. Topics covered include general linear functional estimates, the method of moments, and maximum likelihood estimators.

Feiveson, A. H.↗
NASA NTRS1989

Tele-autonomous control involving contacts: The applications of a high precision laser line range sensor

The object localization algorithm based on line-segment matching is presented. The method is very simple and computationally fast. In most cases, closed-form formulas are used to derive the solution. The method is also quite flexible, because only few surfaces (one or two) need to be accessed (sensed) to gather necessary range data. For example, if the line-segments are extracted from boundaries of a planar surface, only parameters of one surface and two of its boundaries need to be extracted, as compared with traditional point-surface matching or line-surface matching algorithms which need to access at least three surfaces in order to locate a planar object. Therefore, this method is especially suitable for applications when an object is surrounded by many other work pieces and most of the object is very difficult, is not impossible, to be measured; or when not all parts of the object can be reached. The theoretical ground on how to use line range sensor to located an object was laid. Much work has to be done in order to be really useful.

Volz, R. A.↗
NASA NTRS1989

Chronology of volcanism and rift basin propagation - Rungwe volcanic province, East Africa

The spatial and temporal development of along-axis segmentation in youthful continental rifts was investigated using the results of field, remote sensing, and K-Ar geochronology studies conducted in four (Rukwa, Songwe, Usangu, and Karonga) rift basins within the Rungwe volcanic province in East Africa. Results indicated that the Rukwa and Karonga border fault segments formed between 7.25 and 5 m.y. ago, the Usangu border fault segment developed between 3 and 2 m.y. ago, and subsidence along the Songwe border fault segment had occurred by 0.5 Ma. It is shown that individual basins developed diachronously, each following a similar sequence: (1) initial border fault development; (2) asymmetric basin subsidence/flank uplift and the development of monoclines opposite the border faults; and (3) continued subsidence and tilting along intrabasinal faults with flexural upwarping of the rift flanks, enhancing basinal asymmetries.

Ebinger, C. J.↗
NASA NTRS1981

Users manual for the US baseline corn and soybean segment classification procedure

A user's manual for the classification component of the FY-81 U.S. Corn and Soybean Pilot Experiment in the Foreign Commodity Production Forecasting Project of AgRISTARS is presented. This experiment is one of several major experiments in AgRISTARS designed to measure and advance the remote sensing technologies for cropland inventory. The classification procedure discussed is designed to produce segment proportion estimates for corn and soybeans in the U.S. Corn Belt (Iowa, Indiana, and Illinois) using LANDSAT data. The estimates are produced by an integrated Analyst/Machine procedure. The Analyst selects acquisitions, participates in stratification, and assigns crop labels to selected samples. In concert with the Analyst, the machine digitally preprocesses LANDSAT data to remove external effects, stratifies the data into field like units and into spectrally similar groups, statistically samples the data for Analyst labeling, and combines the labeled samples into a final estimate.

Horvath, R.↗
NASA NTRS2012

James Webb Space Telescope: Large Deployable Cryogenic Telescope in Space

The James Webb Space Telescope (JWST) is an infrared space telescope designed to explore four major science themes: first light and reionization, the assembly of galaxies, the birth of stars and protoplanetary systems, and planetary systems and origins of life. JWST is a segmented architecture telescope with an aperture of 6.6 m. It will operate at cryogenic temperature (40 K), achieved via passive cooling, in an orbit about the Earth-Sun second Lagrange point (L2). Passive cooling is facilitated by means of a large sunshield that provides thermal isolation and protection from direct illumination from the Sun. The large size of the telescope and spacecraft systems require that they are stowed for launch in a configuration that fits the Ariane 5 fairing, and then deployed after launch. Routine wavefront sensing and control measurements are used to achieve phasing of the segmented primary mirror and initial alignment of the telescope. A suite of instruments will provide the capability to observe over a spectral range from 0.6- to 27-micron wavelengths with imaging and spectroscopic configurations. An overview is presented of the architecture and selected optical design features of JWST are described

Lightsey, Paul A.↗
NASA NTRS2015

Automated Segmentation and Classification of Coral Using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the worlds coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS1972

A three stage sampling model for remote sensing applications

A conceptual model and an empirical application of the relationship between the manner of selecting observations and its effect on the precision of estimates from remote sensing are reported. This three stage sampling scheme considers flightlines, segments within flightlines, and units within these segments. The error of estimate is dependent on the number of observations in each of the stages.

Eisgruber, L. M.↗
NASA NTRS1990

Adaptive optics and optical structures; Proceedings of the Meeting, European Congress on Optics, 3rd, The Hague, Netherlands, Mar. 12-14, 1990

The present conference on adaptive optics (AO) and optical structures addresses AO systems and controls, AO components, nonlinear optics applications to AO, astronomical applications of AO, large telescopes and optical alignment, as well as the wavefront control experiment for the use of AO in beam propagation. Specific references are made to applications of electromagnetic theory in optics, theoretical studies of system performance and design parameters, Hartmann-Shack wavefront sensing, the use of ray-based techniques in cophasing segmented mirrors, the use of a phase-conjugating mirror for real-time phase visualization, and the absolute instability of oppositely directed waves with respect to a high-reflectivity phase-conjugate mirror. Also addressed are automatic control systems, precision segmented reflectors, AO system creation, the VLT's 8.2-m primary mirrors, an optical 12-m telescope, alignment optimization via the Talbot effect, and a combination of interferometry and ray-tracing analysis.

Tyson, Robert K.↗
NASA NTRS2008

MACOS Version 3.31

Version 3.31 of Modeling and Analysis for Controlled Optical Systems (MACOS) has been released. MACOS is an easy-to-use computer program for modeling and analyzing the behaviors of a variety of optical systems, including systems that have large, segmented apertures and are aligned with the technology of wavefront sensing and control. Two previous versions were described in "Improved Software for Modeling Controlled Optical Systems" (NPO-19841) NASA Tech Briefs, Vol. 21, No. 12 (December 1997), page 42 and "Optics Program Modified for Multithreaded Parallel Computing" (NPO-40572) NASA Tech Briefs, Vol. 30, No. 1 (January 2006) page 13a. The present version incorporates the following enhancements over prior versions: a) A powerful system-optimization facility includes algorithms for linear, nonlinear, unconstrained, and constrained optimization of optical systems under a variety of settings. b) There is now enhanced capability to perturb optical components individually and on subsystem levels, and to optimize system performance by adjusting selected individual components as well as subsystems. c) Capabilities for modeling a variety of new optical aperture types have been added. d) Effects of multilayer thin-film coats on optical surfaces can now be taken into account when tracing polarized rays. e) Major software-engineering work was performed to make MACOS more reliable, flexible, and manageable for purposes of maintenance and further development.

Redding, David↗
NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗
NASA NTRS2012

Earthquake Damage Assessment Using Objective Image Segmentation: A Case Study of 2010 Haiti Earthquake

In this study, we perform a case study on imagery from the Haiti earthquake that evaluates a novel object-based approach for characterizing earthquake induced surface effects of liquefaction against a traditional pixel based change technique. Our technique, which combines object-oriented change detection with discriminant/categorical functions, shows the power of distinguishing earthquake-induced surface effects from changes in buildings using the object properties concavity, convexity, orthogonality and rectangularity. Our results suggest that object-based analysis holds promise in automatically extracting earthquake-induced damages from high-resolution aerial/satellite imagery.

image segmentation↗
NASA NTRS2016

Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗
NASA NTRS2019

Technologies to Enable the Next Great Observatory

The Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR) is one of four mission concepts being studied by NASA for the 2020 Decadal Survey in Astronomy and Astrophysics. LUVOIR will be capable of a broad range of science, including: direct imaging and characterization of a wide range of exoplanets and the search for biosignatures on Earth-like planets around sun-like stars; studying galaxy formation and evolution; investigating star and planet formation; and remote sensing of bodies within the Solar System. Enabling a mission as ambitious as LUVOIR requires an array of technologies, such as ultra-stable structures and optics, precision metrology and wavefront sensing, high-contrast imaging techniques, large-format detectors with very low noise, and high-throughput ultraviolet instrumentation. Critically, a systems-level approach must be taken to developing these technologies, guided by architecture studies to place each technology in the appropriate system context.In this poster, we describe LUVOIR's technology needs, as well as current efforts that are actively developing these technologies. We will discuss recent advancements in: measuring picometer-level displacements of optical and structural elements; sub-milli-kelvin thermal sensing and control; non-contact vibration isolation for pointing and dynamic stability; coronagraph design for achieving 10-10 contrast on a segmented system; high-speed metrology for optical system alignment; low-order and out-of-band wavefront sensing for maintaining high-contrast images; low-noise detectors across the ultraviolet, optical, and near infrared bands; broadband coatings with high-reflectivity below Ly. We will also describe a systems approach to coordinating the development of these technologies to achieve the necessary maturity for a LUVOIR mission start in the next decade.

space telescopes↗
NASA NTRS2011

Testing and Calibration of Phase Plates for JWST Optical Simulator

Three phase plates were designed to simulate the JWST segmented primary mirror wavefront at three on-orbit alignment stages: coarse phasing, intermediate phasing, and fine phasing. The purpose is to verify JWST's on-orbit wavefront sensing capability. Amongst the three stages, coarse alignment is defined to have piston error between adjacent segments being 30 m to 300 m, intermediate being 0.4 m to 10 m, and fine is below 0.4 m. The phase plates were made of fused silica, and were assembled in JWST Optical Simulator (OSIM). The piston difference was realized by the thickness difference of two adjacent segments. The two important parameters to phase plates are piston and wavefront errors. Dispersed Fringe Sensor (DFS) method was used for initial coarse piston evaluation, which is the emphasis of this paper. Point Diffraction Interferometer (PDI) is used for fine piston and wavefront error. In order to remove piston's 2 pi uncertainty with PDI, three laser wavelengths, 640nm, 660nm, and 780nm, are used for the measurement. The DHS test setup, analysis algorithm and results are presented. The phase plate design concept and its application (i.e. verifying the JWST on-orbit alignment algorithm) are described. The layout of JWST OSIM and the function of phase plates in OSIM are also addressed briefly.

Gong, Qian↗
NASA NTRS1991

Refinement of ground reference data with segmented image data

One of the ways to determine ground reference data (GRD) for satellite remote sensing data is to photo-interpret low altitude aerial photographs and then digitize the cover types on a digitized tablet and register them to 7.5 minute U.S.G.S. maps (that were themselves digitized). The resulting GRD can be registered to the satellite image or, vice versa. Unfortunately, there are many opportunities for error when using digitizing tablet and the resolution of the edges for the GRD depends on the spacing of the points selected on the digitizing tablet. One of the consequences of this is that when overlaid on the image, errors and missed detail in the GRD become evident. An approach is discussed for correcting these errors and adding detail to the GRD through the use of a highly interactive, visually oriented process. This process involves the use of overlaid visual displays of the satellite image data, the GRD, and a segmentation of the satellite image data. Several prototype programs were implemented which provide means of taking a segmented image and using the edges from the reference data to mask out these segment edges that are beyond a certain distance from the reference data edges. Then using the reference data edges as a guide, those segment edges that remain and that are judged not to be image versions of the reference edges are manually marked and removed. The prototype programs that were developed and the algorithmic refinements that facilitate execution of this task are described.

Robinson, Jon W.↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗