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NASA NTRS1993

The importance of properties in modeling

Casting and welding of superalloys, stainless steel and titanium alloys are processes which can be improved through modeling of heat flow, fluid flow, residual stress development, and microstructural evolution. These simulations require inputs of thermophysical data, some of which involves the partially or totally liquid state. In particular, these processes involve melting, flow in the liquid, and solidification. Modeling of such processes can lead to an improved understanding of defects such as shrinkage, inclusions, cracks, incomplete filling (or penetration), macrosegregation, improper grain structure, and deviations from dimensional specifications. Effective modeling can shorten process development time and improve quality. An approach to these problems is to develop efficient models; validate through correlations with thermal, distortion, and microstructural data; run parametric studies; extract knowledge based rules; and apply to adaptive closed loop control systems. With the appropriate pre- and post-processing, such analyses can be made 'user friendly'. This would include graphical user interfaces as well as realistic images and color maps. In such form, these models can be used for sensitivity analyses, which are useful in defining appropriate sensors and in the development of control strategies. Such modeling can be done at several levels, e.g., the MARO level, modeling large scale phenomena such as heat and fluid flow or material deformation; the MICRO level, modeling the development of dendrites, grains or precipitates; or at the NANO level, modeling point defects, dislocations, stacking faults, etc. There are many computational issues associated with these simulations, e.g. computational efficiency and accuracy. In addition, there are many materials issues, not the least of which is the availability of accurate high temperature thermophysical data for complex alloys. This would include latent heat of fusion, temperature dependent heat capacity and thermal conductivity (for liquid and solid), viscosity, surface tension, thermal expansion, mechanical properties, etc. Preliminary data is frequently gathered from the literature; however, this is often not available for modern alloys. If additional data are required, measurements can be used; however, these are costly, time consuming and can be erroneous due to a lack of testing standards or impure materials. Microstructural predictors can be extracted from thermal information, e.g. cooling rate and thermal gradient; the prediction of microstructure is dependent on solidus and liquidus temperature, mushy zone permeability, the solidification curve, volume changes, phase transformations, alloying effects (such as surface tension or viscosity), mold/metal reactions, metal/environment reactions, etc. Defect maps may be needed to predict the onset of shrinkage, hot cracking or 'freckling'. Constants may be needed for stress relaxation, dendrite coarsening, vaporization, etc. Visualization was used as a tool to better comprehend complex data sets associated with the analysis of directional solidification (including crystal growth) and welding. Examples include not only isotherms, but also cooling rate, growth rate and thermal gradient. The latter two are not single valued scalars, but rather time and space dependent vector fields. Efficient models were developed for both casting and welding to predict heat flow and the relationship to dendrite and grain growth. These codes include many of the non-linear effects, e.g. radiation, which dominate these processes. The home-built FDM code(s) were designed to be useful not only to the scientist, but also to the process engineer. Special output can be requested to compare directly to experimental data. Visualization procedures were developed to visualize critical results, e.g. fusion zone width at the surface opposite that where the arc is applied ('penetration'). Both elaborate and simplified distortion analyses were carried out. It is clear that extensive mechanical property data are critical in order to accurately predict residual stress patterns. A scheme is currently being developed to integrate these modeling tools into a set of control algorithms; however, the success of this approach is critically dependent on the availability of accurate high temperature thermophysical data.

Giamei, A. F.↗

NASA NTRS2006

Effects of diffraction and static wavefront errors on high-contrast imaging from the Thirty Meter Telescope

High-contrast imaging, particularly direct detection of extrasolar planets, is a major science driver for the next generation of extremely large telescopes such as the segmented Thirty Meter Telescope. This goal requires more than merely diffraction-limited imaging, but also attention to residual scattered light from wavefront errors and diffraction effects at the contrast level of 10-8-10-9. Using a wave-optics simulation of adaptive optics and a diffraction suppression system we investigate diffraction from the segmentation geometry, intersegment gaps, obscuration by the secondary mirror and its supports. We find that the large obscurations pose a greater challenge than the much smaller segment gaps. In addition the impact of wavefront errors from the primary mirror, including segment alignment and figure errors, are analyzed. Segment-to-segment reflectivity variations and residual segment figure error will be the dominant error contributors from the primary mirror. Strategies to mitigate these errors are discussed.

segmented mirrors↗

NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗

NASA NTRS2017

The Use of Altered Gravity as a Tool to Understand Neurovestibular Mechanisms in Vertebrates

Vertebrates sense gravito-inertial acceleration by mechanoreceptors (hair cells) in the otolith structures of the inner ear. These structures consist of ciliated sensory hair cells surmounted by biomineral grains of calcium carbonate (CaCO3) called otoconia that provide mechanical loading of hair cell cilia. Changes in their high density can alter the hair cells sensitivity to acceleration and orientation with respect to gravity. A widely considered mechanism by which the animal responds to a chronic change in amplitude of gravity is a change in weight-lending otoconia. Hair cells are synaptically coupled to the vestibular nerve afferents that convey the signals into the brain. Synapses are modifiable in strength and numbers, and thereby can be an additional target to adjust the sensation as the gravity load changes. Here, we present the results obtained in 2 species exposed both to G and HG. Adult toadfish, Opsanus tau, were exposed to G in 2 short-duration shuttle missions and to 1.4 2.24G [resultant] centrifugation for 1-32 days; re-adaptation was studied following 1-8 days after return to 1G. Results show a biphasic pattern in response to 2.24G: initial hypersensitivity, similar to that observed after G exposure, followed by transition to a significant decrease at 16-32 days. Recovery from HG exposure is 4-8 days. Two major pieces of information are still needed: vertebrate hair cell response to altered gravity and impact of longer duration exposures on sensory plasticity. To address the latter we applied electron microscopic techniques to image otoconia mass obtained from 1) mice subjected to 91-days of weightlessness in the Mouse Drawer System (MDS) flown on International Space Station, 2) mice subjected to 91-days of 1.24G centrifugation on ground, and 3) mice flown on 2 short-duration orbital missions. Images indicate a clear restructuring of individual otoconia, suggesting deposition to the outer shell. Images from their HG counterparts indicate the converse - an ablation of the otoconia mass. For shorter duration exposures to weightlessness on 13-day shuttle missions mice otoconia appear normal. Despite the permanence of 1G in evolution the animal senses exposure to a novel, non-1G, environment and adaptive mechanisms are initiated - in the short term compensation is likely confined to the peripheral sensory receptors, the brain or both. For longer exposures structural modifications of the endorgan may also result.

vertebrate↗

NASA NTRS2022

Wichita Climate II: Quantifying and Mapping Urban Heat to Inform Equitable and Sustainable Urban Planning Initiatives in Wichita, Kansas

Wichita, Kansas is experiencing a host of climate threats, particularly extreme heat manifested through Urban Heat Islands (UHI). Heat is unevenly distributed within cities due to factors such as income inequality, historical discriminatory practices like redlining, and divestment in neighborhoods of color. This leads to less vegetation and more heat-absorbing infrastructure in specific communities. Moreover, adverse effects of heat, including heat-related morbidity and mortality, disproportionately impact populations that experience vulnerability through social inequities and structural discrimination. Heat vulnerability is a combination of the factors of heat exposure, sensitivity, and adaptive capacity, and can be harnessed to guide urban heat interventions. This DEVELOP project partnered with the City of Wichita to understand the spatial distribution and drivers of UHIs and heat vulnerability indicators. The team modeled outcomes of tree cover interventions using Landsat 8’s Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI), Landsat 9 TIRS-2 and OLI-2, and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on the International Space Station (ECOSTRESS) sensor, along with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling model. The team also leveraged statistical analysis by implementing principal component analysis to develop a heat vulnerability index (HVI) specific to Wichita. Ultimately, the project’s outputs will inform the City of Wichita’s Climate Adaptation and Mitigation Plan, identify priority areas for heat mitigation initiatives, and be used in public-facing communications to educate communities on the impacts of urban heat.

Environmental Justice↗

NASA NTRS1992

Interferometers adaptations to lidars

To perform daytime measurements of the density and temperature by Rayleigh lidar, it is necessary to select the wavelength with a very narrow spectral system. This filter is composed by an interference filter and a Fabry Perot etalon. The Fabry Perot etalon is the more performent compound, and it is necessary to build a specific optic around it. The image of the entrance pupil or the field diaphragm is at the infinite and the other diaphragm is on the etalon. The optical quality of the optical system is linked to the spectral resolution of the system to optimize the reduction of the field of view. The resolution is given by the formula: R = 8(xD/Fd)exp 2 where R = lambda/delta(lambda), x = diameter of the field diaphragm, D = diameter of the reception mirror, F = focal length of the telescope, and d = useful diameter of the etalon. In the Doppler Rayleigh lidars, the PF interferometer is the main part of the experiment and the exact spectral adaptation is the most critical problem. In the spectral adaptation of interferometers, the transmittance of the system will be acceptable if the etalon is exactly adjusted to the wavelength of the laser. It is necessary to work with a monomode laser, and adjust the shift to the bandpass of the interferometer. We are working with an interferometer built with molecular optical contact. This interferometer is put in a special pressure closed chamber.

Porteneuve, J.↗

DOE OSTI2024

Improved constraints on hematite refractive index for estimating climatic effects of dust aerosols

Abstract Uncertainty in desert dust composition poses a big challenge to understanding Earth’s climate across different epochs. Of particular concern is hematite, an iron-oxide mineral dominating the solar absorption by dust particles, for which current estimates of absorption capacity vary by over two orders of magnitude. Here, we show that laboratory measurements of dust composition, absorption, and scattering provide valuable constraints on the absorption potential of hematite, substantially narrowing its range of plausible values. The success of this constraint is supported by results from an atmospheric transport model compared with station-based measurements. Additionally, we identify substantial bias in simulating hematite abundance in dust aerosols with current soil mineralogy descriptions, underscoring the necessity for improved data sources. Encouragingly, the next-generation imaging spectroscopy remote sensing data hold promise for capturing the spatial variability of hematite. These insights have implications for enhancing dust modeling, thus contributing to efforts in climate change mitigation and adaptation.

Environmental Sciences & Ecology↗

NASA NTRS2008

Fomalhaut's Debris Disk and Planet: Constraining the Mass of Formalhaut B from Disk Morphology

Following the optical imaging of exoplanet candidate Fomalhaut b (Fom b), we present a numerical model of how Fomalhaut's debris disk is gravitationally shaped by a single interior planet. The model is simple, adaptable to other debris disks, and can be extended to accommodate multiple planets. If Fom b is the dominant perturber of the belt, then to produce the observed disk morphology it must have a mass M(sub pl) < 3M(sub J), an orbital semimajor axis a(sub pl) > 101.5AU, and an orbital eccentricity e(sub pl) = 0.11 - 0.13. These conclusions are independent of Fom b's photometry. To not disrupt the disk, a greater mass for Fom b demands a smaller orbit farther removed from the disk; thus, future astrometric measurement of Fom b's orbit, combined with our model of planet-disk interaction, can be used to determine the mass more precisely. The inner edge of the debris disk at a approximately equals 133AU lies at the periphery of Fom b's chaotic zone, and the mean disk eccentricity of e approximately equals 0.11 is secularly forced by the planet, supporting predictions made prior to the discovery of Fom b. However, previous mass constraints based on disk morphology rely on several oversimplifications. We explain why our constraint is more reliable. It is based on a global model of the disk that is not restricted to the planet's chaotic zone boundary. Moreover, we screen disk parent bodies for dynamical stability over the system age of approximately 100 Myr, and model them separately from their dust grain progeny; the latter's orbits are strongly affected by radiation pressure and their lifetimes are limited to approximately 0.1 Myr by destructive grain-grain collisions. The single planet model predicts that planet and disk orbits be apsidally aligned. Fomalhaut b's nominal space velocity does not bear this out, but the astrometric uncertainties are difficult to quantify. Even if the apsidal misalignment proves real, our calculated upper mass limit of 3 M(sub J) still holds. Parent bodies are evacuated from mean-motion resonances with Fom b; these empty resonances are akin to the Kirkwood gaps opened by Jupiter. The belt contains at least 3M(sub Earth) of solids that are grinding down to dust, their velocity dispersions stirred so strongly by Fom b that collisions are destructive. Such a large mass in solids is consistent with Fom b having formed in situ.

Chiang, E.↗

DOE OSTI2020

Development and Validation of Quantitative Model-Based Image Reconstruction for NDE of Reinforced Steel-Lined Concrete Structures: Kal-El FY 2020

This project studied the capabilities of Model-Based Image Reconstruction (MBIR) and Machine Learning (ML) algorithms in the imaging and estimation of rebar corrosion from ultrasound signals. The application was challenging due to the introduction of a steel liner between the sensor and the concrete containing the rebar. The study focused in a synthetic specimen with a 6.35 mm thick steel liner, and a 19.05 mm diameter rebar at a depth of 44.5 mm and with four levels of corrosion; 0%, 20%, 50%, and 100% corrosion level. The corrosion was applied uniformly around the rebar, generating a ring in the perimeter of the rebar with different acoustic density. In order to generate a realistic synthetic dataset, we added random texture to the concrete of the synthetic specimens. This texture will mimic the variations encountered in real concrete specimens.We adapted our MBIR algorithm for the application and enhanced the algorithm to integrate in the physical model known specimen features, such as the steel liner thickness. The new MBIR method was able to cancel out reverberation from the steel liner and properly image the rebar. In particular, corrosion for the 50% and 100% cases were easily visible and quantitative metrics showed a slight separation for the 0% and 20% levels. The quantitative results were in agreement with the qualitative assessment. We also developed a ML XGBoost model to estimate corrosion level from the ultrasound signals. By combining the ML method with MBIR, we can pinpoint in the ultrasound signals the section that corresponds to the echoes from the rebar. The extract signals are processed by the XGBoost model for prediction. From each system scan, we obtain 15 predictions. The median prediction value is used as the final prediction. The True Acceptance Rate for the method is over 99%.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Visibility of wavelet quantization noise

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

NASA Center ARC↗

DOE OSTI2022

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa ( Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Efficient Synthesis and HPLC-Based Characterization for Developing Vanadium-48-Labeled Vanadyl Acetylacetonate as a Novel Cancer Radiotracer for PET Imaging

Bis(acetylacetonato)oxidovanadium(IV) [(VO(acac) 2 ], generally known as vanadyl acetylacetonate, has been shown to be preferentially sequestered in malignant tissue. Vanadium-48 ( 48 V) generated with a compact medical cyclotron has been used to label VO(acac) 2 as a potential radiotracer in positron emission tomography (PET) imaging for the detection of cancer, but requires lengthy synthesis. Current literature protocols for the characterization of VO(acac) 2 require macroscale quantities of reactants and solvents to identify products by color and to enable crystallization that are not readily adaptable to the needs of radiotracer synthesis. We present an improved method to produce vanadium-48-labeled VO(acac) 2 , [ 48 V]VO(acac) 2 , and characterize it using high-performance liquid chromatography (HPLC) with radiation detection in combination with UV detection. The approach is suitable for radiotracer-level quantities of material. These methods are readily applicable for production of [ 48 V]VO(acac) 2 . Preliminary results of preclinical, small-animal PET studies are presented.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

Editorial overview: Unlocking the secrets of nongenetic plasticity, one cell at a time

Cellular noise, the non-genetic variability observed among isogenic cells, arises from factors such as growth conditions, aging, and stochastic gene expression, influencing cell stress-response, metabolism, morphology, and size. Here, such plasticity, while critical for adaptation, often goes unnoticed with traditional population-averaging biotechnologies that inevitably mask cell-specific variations and prompting the question, "What else might we be missing". However, recent breakthroughs in optical imaging, microfluidics, and omics, are beginning to uncover the complexity of cellular plasticity. This special is-sue highlights some of these breakthroughs, with key contributions including innovations in multimodal chemical imaging, label-free microscopy, spatial and temporal omics, and droplet-based microfluidics. Collectively, these cutting-edge tools provide unprecedent-ed insights into non-genetic cell-to-cell variability, enhancing our understanding of cellu-lar plasticity and its implications for health, energy, and ecology.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1984

Advanced communications technologies for image processing

It is essential for image analysts to have the capability to link to remote facilities as a means of accessing both data bases and high-speed processors. This can increase productivity through enhanced data access and minimization of delays. New technology is emerging to provide the high communication data rates needed in image processing. These developments include multi-user sharing of high bandwidth (60 megabits per second) Time Division Multiple Access (TDMA) satellite links, low-cost satellite ground stations, and high speed adaptive quadrature modems that allow 9600 bit per second communications over voice-grade telephone lines.

Likens, W. C.↗

NASA NTRS1992

Identification and control of a multizone crystal growth furnace

This paper presents an intelligent adaptive control system for the control of a solid-liquid interface of a crystal while it is growing via directional solidification inside a multizone transparent furnace. The task of the process controller is to establish a user-specified axial temperature profile and to maintain a desirable interface shape. Both single-input-single-output and multi-input-multi-output adaptive pole placement algorithms have been used to control the temperature. Also described is an intelligent measurement system to assess the shape of the crystal while it is growing. A color video imaging system observes the crystal in real time and determines the position and the shape of the interface. This information is used to evaluate the crystal growth rate, and to analyze the effects of translational velocity and temperature profiles on the shape of the interface. Creation of this knowledge base is the first step to incorporate image processing into furnace control.

Batur, C.↗

NASA NTRS1994

Active weld control

Through the two phases of this contract, sensors for welding applications and parameter extraction algorithms have been developed. These sensors form the foundation of a weld control system which can provide action weld control through the monitoring of the weld pool and keyhole in a VPPA welding process. Systems of this type offer the potential of quality enhancement and cost reduction (minimization of rework on faulty welds) for high-integrity welding applications. Sensors for preweld and postweld inspection, weld pool monitoring, keyhole/weld wire entry monitoring, and seam tracking were developed. Algorithms for signal extraction were also developed and analyzed to determine their application to an adaptive weld control system. The following sections discuss findings for each of the three sensors developed under this contract: (1) weld profiling sensor; (2) weld pool sensor; and (3) stereo seam tracker/keyhole imaging sensor. Hardened versions of these sensors were designed and built under this contract. A control system, described later, was developed on a multiprocessing/multitasking operating system for maximum power and flexibility. Documentation for sensor mechanical and electrical design is also included as appendices in this report.

Powell, Bradley W.↗

DOE OSTI2021

Spatial Mode Correction of Single Photons Using Machine Learning

Abstract Spatial modes of light constitute valuable resources for a variety of quantum technologies ranging from quantum communication and quantum imaging to remote sensing. Nevertheless, their vulnerabilities to phase distortions, induced by random media, impose significant limitations on the realistic implementation of numerous quantum‐photonic technologies. Unfortunately, this problem is exacerbated at the single‐photon level. Over the last two decades, this challenging problem has been tackled through conventional schemes that utilize optical nonlinearities, quantum correlations, and adaptive optics. In this article, the self‐learning and self‐evolving features of artificial neural networks are exploited to correct the complex spatial profile of distorted Laguerre–Gaussian modes at the single‐photon level. Furthermore, the potential of this technique is used to improve the channel capacity of an optical communication protocol that relies on structured single photons. The results have important implications for real‐time turbulence correction of structured photons and single‐photon images.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1979

Charge-coupled device /CCD/ trackers for high accuracy guidance applications

Recent advances in large area charge coupled device (CCD) imaging detectors and high speed microprocessors have prompted the development of a new class of electro-optical tracking instruments at the Jet Propulsion Laboratory (JPL). These instruments are designed for standardized NASA-wide usage and are characterized by their extremely high pointing accuracy and stability and performance capabilities which are largely software defined and thus easily adapted to a variety of mission requirements. This paper presents an examination of the methods by which CCD detectors are being incorporated in star tracker instruments and the performance capabilities that can be expected from currently available devices. The multi-function sensor concept, in which a single sensor can function in a variety of guidance applications, is described. Software algorithms designed to provide efficient extraction of guidance information from both point and extended images are also presented. CCD star tracker implementations currently underway at JPL are described, and performance data obtained during laboratory testing is presented and discussed.

Salomon, P. M.↗