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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Motion detection, novelty filtering, and target tracking using an interferometric technique with GaAs phase conjugate mirror

A method and apparatus for detecting and tracking moving objects in a noise environment cluttered with fast- and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photorefractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the interferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Cheng, Li-Jen↗
NASA NTRS2008

Crack Offset Measurement With the Projected Laser Target Device

The device and associated analysis methodology summarized in this report were developed for the purpose of estimating the size of discontinuities in the surface of the foam that covers the Space Shuttle External Tank. These surface offsets are thought to be due to subsurface cracks in the foam insulation. The mathematical analysis and procedure described here provide a method to quantity the dimensions of the crack offset in a direction perpendicular to the surface, making use of the projected laser target device (PLTD) tool and a laser line projector. The keys to the construction and use of the PLTD are the following geometrical design requirements: Laser dots are on a square grid: length on a side. Laser beams are perpendicular to projected surface. Beams are parallel out to the distance being projected. The PLTD can be used to (1) calibrate fixed cameras of unknown magnification and orientation (far-field solution); (2) provide equivalent calibration to multiple cameras, previously achieved only by the use of known target points, for example, in 3.D foreign-object debris tracking on a fixed launch platform; (3) compute scaling for conventional 2.D images, and depth of field for 3.D images (near-field solution); and (4) in conjunction with a laser line projector, achieve accurate measurements of surface discontinuity (cracks) in a direction perpendicular to the surface.

Source record↗
NASA NTRS2012

Wavefront Compensation Segmented Mirror Sensing and Control

The primary mirror of very large submillimeter-wave telescopes will necessarily be segmented into many separate mirror panels. These panels must be continuously co-phased to keep the telescope wavefront error less than a small fraction of a wavelength, to ten microns RMS (root mean square) or less. This performance must be maintained continuously across the full aperture of the telescope, in all pointing conditions, and in a variable thermal environment. A wavefront compensation segmented mirror sensing and control system, consisting of optical edge sensors, Wavefront Compensation Estimator/Controller Soft ware, and segment position actuators is proposed. Optical edge sensors are placed two per each segment-to-segment edge to continuously measure changes in segment state. Segment position actuators (three per segment) are used to move the panels. A computer control system uses the edge sensor measurements to estimate the state of all of the segments and to predict the wavefront error; segment actuator commands are computed that minimize the wavefront error. Translational or rotational motions of one segment relative to the other cause lateral displacement of the light beam, which is measured by the imaging sensor. For high accuracy, the collimator uses a shaped mask, such as one or more slits, so that the light beam forms a pattern on the sensor that permits sensing accuracy of better than 0.1 micron in two axes: in the z or local surface normal direction, and in the y direction parallel to the mirror surface and perpendicular to the beam direction. Using a co-aligned pair of sensors, with the location of the detector and collimated light source interchanged, four degrees of freedom can be sensed: transverse x and y displacements, as well as two bending angles (pitch and yaw). In this approach, each optical edge sensor head has a collimator and an imager, placing one sensor head on each side of a segment gap, with two parallel light beams crossing the gap. Two sets of optical edge sensors are used per segment-to-segment edge, separated by a finite distance along the segment edge, for four optical heads, each with an imager and a collimator. By orienting the beam direction of one edge sensor pair to be +45 away from the segment edge direction, and the other sensor pair to be oriented -45 away from the segment edge direction, all six degrees of freedom of relative motion between the segments can be measured with some redundancy. The software resides in a computer that receives each of the optical edge sensor signals, as well as telescope pointing commands. It feeds back the edge sensor signals to keep the primary mirror figure within specification. It uses a feed-forward control to compensate for global effects such as decollimation of the primary and secondary mirrors due to gravity sag as the telescope pointing changes to track science objects. Three segment position actuators will be provided per segment to enable controlled motions in the piston, tip, and tilt degrees of freedom. These actuators are driven by the software, providing the optical changes needed to keep the telescope phased.

Redding, David C.↗
NASA NTRS2013

A Short-Range Distance Sensor with Exceptional Linearity

A sensor has been demonstrated that can measure distance over a total range of about 300 microns to an accuracy of about 0.1 nm (resolution of about 0.01 nm). This represents an exceptionally large dynamic range of operation - over 1,000,000. The sensor is optical in nature, and requires the attachment of a mirror to the object whose distance is being measured. This work resulted from actively developing a white light interferometric system to be used to measure the depths of defects in the Space Shuttle Orbiter windows. The concept was then applied to measuring distance. The concept later expanded to include spectrometer calibration. In summary, broadband (i.e., white) light is launched into a Michelson interferometer, one mirror of which is fixed and one of which is attached to the object whose distance is to be measured. The light emerging from the interferometer has traveled one of two distances: either the distance to the fixed mirror and back, or the distance to the moving mirror and back. These two light beams mix and produce an interference pattern where some wavelengths interfere constructively and some destructively. Sending this light into a spectrometer allows this interference pattern to be analyzed, yielding the net distance difference between the two paths. The unique feature of this distance sensor is its ability to measure accurately distance over a dynamic range of more than one million, the ratio of its range (about 300 microns) to its accuracy (about 0.1 nanometer). Such a large linear operating range is rare and arises here because both amplitude and phase-matching algorithms contribute to the performance. The sensor is limited by the need to attach a mirror of some kind to the object being tracked, and by the fairly small total range, but the exceptional dynamic range should make it of interest.

Simmons, Steven↗
NASA NTRS2015

Proposed SLR Optical Bench Required to Track Debris Using 1550 nm Lasers

A previous study has indicated that by using approx.1550 nm wavelengths a laser ranging system can track debris objects in an "eye safe" manner, while increasing the expected return rate by a factor of approx. 2/unit area of the telescope. In this presentation we develop the optical bench required to use approx.1550nm lasers, and integration with a 532nm system. We will use the optical bench configuration for NGSLR as the baseline, and indicate a possible injection point for the 1550 nm laser. The presentation will include what elements may need to be changed for transmitting the required power on the approx.1550nm wavelength, supporting the alignment of the laser to the telescope, and possible concerns for the telescope optics.

Satellite Laser Ranging↗
NASA NTRS2016

The Orion Exploration Flight Test Post Flight Solid Particle Flight Environment Inspection and Analysis

Orbital debris in the millimeter size range can pose a hazard to current and planned spacecraft due to the high relative impact speeds in Earth orbit. Fortunately, orbital debris has a relatively short life at lower altitudes due to atmospheric effects; however, at higher altitudes orbital debris can survive much longer and has resulted in a band of high flux around 700 to 1,500 km above the surface of the Earth. While large orbital debris objects are tracked via ground based observation, little information can be gathered about small particles except by returned surfaces, which until the Orion Exploration Flight Test number one (EFT-1), has only been possible for lower altitudes (400 to 500 km). The EFT-1 crew module backshell, which used a porous, ceramic tile system with surface coatings, has been inspected post-flight for potential micrometeoroid and orbital debris (MMOD) damage. This paper describes the pre- and post-flight activities of inspection, identification and analysis of six candidate MMOD impact craters from the EFT-1 mission.

Miller, Joshua E.↗
NASA NTRS2017

SO-QT: Collaborative Tool to Project the Future Space Object Population

Earth orbit gets increasingly congested, a challenge to space operators, both in governments and industry. We present a web tool that provides: 1) data on todays and the historic space object environments, by aggregating object-specific tracking data; and 2) future trends through a collaboration platform to collect information on planed launches. The collaborative platform enables experts to pool and compare their data in order to generate future launch scenarios. The tool is intended to support decision makers and mission designers while they investigate future missions and scholars as they develop strategies for space traffic management.

space debris↗
NASA NTRS2018

Performance of Variable Coded Modulations over a Nonlinear Channel for VCM Protocol Red Book

This presentation provides a summary of the results obtained from a study which evaluates the performance of variable coded modulations specified in the "Variable Coded Modulation Protocol" CCSDS Red Book, over a nonlinear channel that is currently on the CCSDS Blue Book track. The objectives are to perform simulation that identifies the operating signal-to-noise-power ratio required to achieve a codeword error rate of 1e-4 over the specified nonlinear channel for various modulations (i.e. BPSK, QPSK, 8-PSK) and LDPC coding schemes, and compare against performance over an ideal additive white Gaussian channel. We select a only subset of operating modes to perform the analysis which are based on a number of mitigation techniques to combat the nonlinear distortions. Specifically, transmitter centroidal pre-distortion, phase post-distortion and receiver mean phase estimation are analyzed in this study.

coding↗
NASA NTRS2018

Observations of Fast-Moving Features in the Debris Disk of AU Mic on a Three-Year Timescale: Confirmation and New Discoveries

Context. The nearby and young M star AU Mic is surrounded by a debris disk in which we previously identified a series of large-scale arch-like structures that have never been seen before in any other debris disk and that move outward at high velocities. Aims. We initiated a monitoring program with the following objectives: (1) track the location of the structures and better constrain their projected speeds, (2) search for new features emerging closer in, and ultimately (3) understand the mechanism responsible for the motion and production of the disk features. Methods. AU Mic was observed at 11 different epochs between August 2014 and October 2017 with the IR camera and spectrograph of SPHERE. These high-contrast imaging data were processed with a variety of angular, spectral, and polarimetric differential imaging techniques to reveal the faintest structures in the disk. We measured the projected separations of the features in a systematic way for all epochs. We also applied the very same measurements to older observations from the Hubble Space Telescope (HST) with the visible cameras STIS and ACS. Results. The main outcomes of this work are (1) the recovery of the five southeastern broad arch-like structures we identified in our first study, and confirmation of their fast motion (projected speed in the range 4–12 km/s); (2) the confirmation that the very first structures observed in 2004 with ACS are indeed connected to those observed later with STIS and now SPHERE; (3) the discovery of two new very compact structures at the northwest side of the disk (at 0.40′′ and 0.55′′ in May 2015) that move to the southeast at low speed; and (4) the identification of a new arch-like structure that might be emerging at the southeast side at about 0.4′′ from the star (as of May 2016). Conclusions. Although the exquisite sensitivity of SPHERE allows one to follow the evolution not only of the projected separation, but also of the specific morphology of each individual feature, it remains difficult to distinguish between possible dynamical scenarios that may explain the observations. Understanding the exact origin of these features, the way they are generated, and their evolution over time is certainly a significant challenge in the context of planetary system formation around M stars.

Boccaletti, A.↗
NASA NTRS2020

NASA’s High-Resolution GEOS Forecasting and Reanalysis Products: Impact of Stratospheric Intrusions on Surface Ozone Air Quality

A new approach to the study of stratospheric intrusions (SIs)? the introduction of ozone-rich lower stratospheric air into the troposphere ? uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics in the UTLS region that generate SIs and the different mechanisms through which SIs may influence tropospheric chemistry and surface air quality. In particular, SIs have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events. While the spring over the western USA does exhibit the largest number of SIs affecting the lower troposphere, we demonstrate that the number of intrusions in the remaining seasons and over the eastern USA is sizable. Using a multitude of observational datasets, including lidar data, ozonesondes and air quality monitoring surface sites, in combination with GEOS forecast and reanalysis products, the transport of ozone from the stratosphere toward the surface is assessed. By focusing on recent reports of high ozone at monitoring station sites likely associated with SIs, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources.

Knowland, K. Emma↗
NASA NTRS2019

Development of a realistic set of synthetic earth impactor orbits

We present a refined method for creating orbits of fictitious Earth impactors that are representative of the actual impactor population. Such orbits are crucial inputs to a variety of investigations, such as those that seek to discern how well and how early a particular asteroid survey can detect impactors, or to understand the progression of impact probability as an object is tracked after discovery.

Jedicke, Robert↗
NASA NTRSDate not supplied

Imagery Analysis for Space Operations

The purpose of this project is to build a prototype camera system that utilizes artificial intelligence/machine learning and computer vision to track an object in 2D and recreate it in 3D.The goal is to improve image analysis and photogrammetry function for Pad 39B operations

Robotics↗
NASA NTRSDate not supplied

Imagery Analysis for Space Operations

The purpose of this project is to build a prototype camera system that utilizes artificial intelligence/machine learning and computer vision to track an object in 2D and recreate it in 3D.The goal is to improve image analysis and photogrammetry function for Pad 39B operations.

Computer Programming↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗
NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗