Search NASA⌕ Search

SEARCH · Search NASA

Results for “optical networking”

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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Deploying the NASA Meter Class Autonomous Telescope (MCAT) on Ascension Island

NASA has successfully constructed the 1.3m Meter Class Autonomous Telescope (MCAT) facility on Ascension Island in the South Atlantic Ocean. MCAT is an optical telescope designed specifically to collect ground-based data for the statistical characterization of orbital debris ranging from Low Earth Orbit (LEO) through Middle Earth Orbits (MEO) and beyond to Geo Transfer and Geosynchronous Orbits (GTO/GEO). The location of Ascension Island has two distinct advantages. First, the near-equatorial location fills a significant longitudinal gap in the Ground-based Electro-Optical Deep Space Surveillance (GEODSS) network of telescopes, and second, it allows access to objects in Low Inclination Low-Earth Orbits (LILO). The MCAT facility will be controlled by a sophisticated software suite that operates the dome and telescope, assesses sky and weather conditions, conducts all necessary calibrations, defines an observing strategy (as dictated by weather, sky conditions and the observing plan for the night), and carries out the observations. It then reduces the collected data via four primary observing modes ranging from tracking previously cataloged objects to conducting general surveys for detecting uncorrelated debris. Nightly observing plans, as well as the resulting text file of reduced data, will be transferred to and from Ascension, respectively, via a satellite connection. Post-processing occurs at NASA Johnson Space Center. Construction began in September, 2014 with dome and telescope installation occurring in April through early June, 2015. First light was achieved in June, 2015. Acceptance testing, full commissioning, and calibration of this soon-to-be fully autonomous system commenced in summer 2015. The initial characterization of the system from these tests is presented herein.

Lederer, S. M.↗
NASA NTRS2011

Navigation Strategies for Primitive Solar System Body Rendezvous and Proximity Operations

A wealth of scientific knowledge regarding the composition and evolution of the solar system can be gained through reconnaissance missions to primitive solar system bodies. This paper presents analysis of a baseline navigation strategy designed to address the unique challenges of primitive body navigation. Linear covariance and Monte Carlo error analysis was performed on a baseline navigation strategy using simulated data from a· design reference mission (DRM). The objective of the DRM is to approach, rendezvous, and maintain a stable orbit about the near-Earth asteroid 4660 Nereus. The outlined navigation strategy and resulting analyses, however, are not necessarily limited to this specific target asteroid as they may he applicable to a diverse range of mission scenarios. The baseline navigation strategy included simulated data from Deep Space Network (DSN) radiometric tracking and optical image processing (OpNav). Results from the linear covariance and Monte Carlo analyses suggest the DRM navigation strategy is sufficient to approach and perform proximity operations in the vicinity of the target asteroid with meter-level accuracy.

Getzandanner, Kenneth M.↗
NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗
NASA NTRS2024

Modeling Atmospheric Brown Carbon in the GISS ModelE Earth System Model

Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 W m −2 . Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper.

brown carbon aerosols↗
NASA NTRS1992

Neural network architectures to analyze OPAD data

A prototype Optical Plume Anomaly Detection (OPAD) system is now installed on the space shuttle main engine (SSME) Technology Test Bed (TTB) at MSFC. The OPAD system requirements dictate the need for fast, efficient data processing techniques. To address this need of the OPAD system, a study was conducted into how artificial neural networks could be used to assist in the analysis of plume spectral data.

Whitaker, Kevin W.↗
NASA NTRS1999

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗
NASA NTRS1998

Airborne lidar observations of smoke haze during SCAR-B 1995

The Smoke, Clouds, Aerosol, and Radiation Brazil(SCAR-B) field campaign was conducted to study the effects that widespread and persistent biomass burning have upon radiative and chemical processes in the atmosphere. The radiative transfer characteristics of the atmosphere are altered by the introduction of particulate and gaseous materials which are the products of the combustion of vegetative material at ground level. These substances are transported and distributed horizontally and vertically by atmospheric dynamical processes which may be perturbed by the heat energy from the fires. As the pollutants disperse, their physical and chemical properties change substantially. A complete description of the effects of smoke requires that the evolution back to the natural situation be fully examined. A most important component of smoke haze investigation is finding its vertical and horizontal distribution in relation to the driving factors of dynamics and the related horizontal transport. In this presentation, we employ data from the Cloud Lidar System(CLS), carried aboard the NASA ER-2 aircraft, to provide a unique view of the particulate or aerosol loading produced by fires, especially with regard to the geometrical distribution of the aerosols in the vertical plane. The lidar has the ability to measure aerosol optical properties in a continuous fashion at quite fine vertical and horizontal resolution. The results from the lidar provide measurements that are largely independent of influences that corrupt passive instruments and thus it can serve to corroborate their results. The extended horizontal and vertical range of lidar results can also augment ground based and airborne in situ measurements which have limited horizontal and vertical scope. We present the results of our analysis of CLS observations taken during the SCAR-B field campaign. Observations of the the aerosol optical thickness from the Aerosol Robotic Network(AERONET) of solar photometers are employed in conjunction with CLS data to derive extinction to backscatter ratio values which are used to convert the lidar backscatter coefficient into extinction coefficient. The extinction coefficient is integrated vertically to find aerosol optical thickness along ER-2 flight tracks. We use images of the CLS derived extinction coefficient to depict its horizontal and vertical distribution. Multispectral photometer optical thickness is used to compute the Angstrom exponent. With these, we examine the hypothesis that the values of extinction to backscatter ratio can be related to the Anstrom coefficient since both of these would be a function of the refractive index and size distribution of the aerosols.

Hart, William D.↗
NASA NTRS1993

Self-Amplified Optical Pattern Recognizer

Self-amplified optical pattern recognizers developed for use in recognition of patterns, in optical computing, and in optoelectronic neural networks. In recognizer, photorefractive crystal serves as medium in which one holographically records diffraction-grating filter representing pattern with which recognition sought. Apparatus "self-amplified" because signal amplified within filter to many orders of magnitude greater than in prior optical pattern recognizers. Basic principle of operation applicable to many types of correlation filters, including (but not limited to) Vander Lugt matched filters, joint-transform filters, and phase-only filters.

Liu, Hua-Kuang↗
NASA NTRS2002

Validation of TOMS Aerosol Products using AERONET Observations

The Total Ozone Mapping Spectrometer (TOMS) aerosol algorithm uses measurements of radiances at two near UV channels in the range 331-380 nm to derive aerosol optical depth and single scattering albedo. Because of the low near UV surface albedo of all terrestrial surfaces (between 0.02 and 0.08), the TOMS algorithm has the capability of retrieving aerosol properties over the oceans and the continents. The Aerosol Robotic Network (AERONET) routinely derives spectral aerosol optical depth and single scattering albedo at a large number of sites around the globe. We have performed comparisons of both aerosol optical depth and single scattering albedo derived from TOMS and AERONET. In general, the TOMS aerosol products agree well with the ground-based observations, Results of this validation will be discussed.

Bhartia, P. K.↗
NASA NTRS2020

Free-Space Optical Communication for CubeSats in Low Lunar Orbit (LLO)

The NASA ARTEMIS Program will include LunaNet, a highly extensible, open architecture, lunar communications and navigation network. A constellation of CubeSats in Low Lunar Orbit (LLO), 100 km, could form an optical communications and navigation network as part of LunaNet, with terminals on the lunar surface, including mobile ones such as with astronauts and rovers. The proposed CubeSat nodes should provide data relay and navigational aid services. The proposed effort herein is to develop a fine pointing capability for laser beam pointing to augment body pointing by CubeSats. Body pointing was used by Aerospace Corporation for the CubeSats in LEO in NASA’s Optical Communications and Sensors Demonstration (OCSD) program [1]. Previously, this fine pointing capability was computer simulated for the OCSD program [2,3]. With fine pointing, the spot size on the Earth was reduced by a factor of eight with a reduction in laser output power by a factor of sixty-four, thereby mitigating the thermal load challenge on the CubeSats. The same reductions in spot size and laser output power can be achieved for CubeSats in LLO. A new method is described for optical data transmissions from satellites, which uses laser arrays for laser beam pointing. It combines a lens system and an array of vertical-cavity, surface-emitting lasers and photodetectors, an VCSEL/Photodetector Array, (both mature technologies), in a novel way. This system is applied to CubeSats in low lunar orbit, (LLO), which use body pointing. Also, It may be able to replace current architectures which use dynamical systems, (i.e., moving parts) to point the laser, and which may also use vibration isolation platforms. The computer simulations used the optics code, OpticStudio, from Zemax, LLC, which has the capabilities to model the laser source and diffraction effects from wave optics. These capabilities make it possible to model laser beam propagation over long space communication distances.

Goorjian, P. M.↗
NASA NTRS2016

Nanoradian Ground-Based Astrometry, Optical Navigation, and Artificial Reference Stars

Spacecraft carrying optical communication lasers can be treated as artificial stars, whose relative astrometry to Gaia reference stars provides spacecraft positions in the plane-of-sky for optical navigation. To be comparable to current Deep Space Network delta-Differential One-way Ranging measurements, thus sufficient for navigation, nanoradian optical astrometry is required. Here we describe our error budget, techniques for achieving nanoradian level ground-base astrometry, and preliminary results from a 1 m telescope. We discuss also how these spacecraft may serve as artificial reference stars for adaptive optics, high precision astrometry to detect exoplanets, and tying reference frames defined by radio and optical measurements.

optical navigation↗
NASA NTRS2011

Polished Panel Optical Receiver for Simultaneous RF/Optical Telemetry with Large DSN Antennas

The polished panel optical receiver concept described here makes use of aluminum panels on the main reflector of the Deep Space Network's (DSN's) 34-meter antennas at optical wavelengths by polishing and coating their surface to efficiently reflect near-infrared wavelengths in the 1,064 1,550-nanometer range. Achievable surface smoothness is not a limiting factor for aluminum panels, and initial field experiments indicate that the surface quality of microwave aluminum panels is sufficient to concentrate the light into small, but not diffraction-limited, spots at their primary focus. Preliminary analysis of data from high-quality microwave panels has shown that the light can be concentrated into 200 400 microradian cones, resulting in spot diameters of 2-4 mm at the 10-meter primary focus F(0) shown in the figure, or 2-4 cm spots at F(1) after magnification by the subreflector, which results in an effective focal length of about 100 meters. Three distinct implementation options are possible, with theoretically identical tracking and communications performance: Option 1: The communications assembly could be placed directly behind the subreflector at F(0), but this placement would require replacing the existing all-aluminum subreflector with a new design that transmits optical wavelengths but reflects RF, thus transmitting the optical signal to the primary focus of the parabolic polished aluminum panels at F(0), as shown in the figure. Option 2: Alternately, the optical communications assembly could be located near the first available focal-spot F(1) following reflection by the subreflector (which would have to be polished), next to the input to the beam waveguide on the main reflector as shown in the figure. Option 3: Finally, the optical communications assembly could be placed inside the pedestal room, and separated from the RF signal after the ellipsoid and before the signal reached the microwave receiver via an RF/optical dichroic near F(3).

Vilnrotter, Victor A.↗
NASA NTRS1971

Short time-scale optical pulsations in the night sky background

A network of monitoring stations designed to detect large scale fluorescence emission in the atmosphere has been in operation for over two years. The motivation for the search arises from the prediction that an energetic photon burst would be produced in a supernova and this burst, when absorbed in the atmosphere, would produce fluorescence. This paper reports on observations up to February 1971. No supernova-like events have been found, although 4.4 were expected. One class of non-fluorescence events is described that evidence suggests is related to electrical discharge in the atmosphere. Another type of non-fluorescence pulse appears to be related to particle precipitation in the atmosphere.

Bertsch, D. L.↗
NASA NTRS1999

Optical Properties of Aerosols from Long Term Ground-Based Aeronet Measurements

AERONET is an optical ground-based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions including AEROCAN (AERONET CANada) and PHOTON (PHOtometrie pour le Traiteinent Operatonnel de Normalisation Satellitaire). The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities purchased for their own monitoring and research objectives. Data are transmitted hourly through the data collection system (DCS) on board the geostationary meteorological satellites GMS, GOES and METEOSAT and received in a common archive for daily processing utilizing a peer reviewed series of algorithms thus imposing a standardization and quality control of the product data base. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. Access to the AERONET data base has shifted from the interactive program 'demonstrat' (reserved for PI's) to the AERONET homepage allowing faster access and greater development for GIS object oriented retrievals and analysis with companion geocoded data sets from satellites, LIDAR and solar flux measurements for example. We feel that a significant yet under utilized component of the AERONET data base are inversion products made from hourly principal plane and almucanter measurements. The current inversions have been shown to retrieve aerosol volume size distributions. A significant enhancement to the inversion code has been developed and is presented in these proceedings.

Holben, B. N.↗
NASA NTRS2010

Identifying Aerosol Type/Mixture from Aerosol Absorption Properties Using AERONET

Aerosols are generated in the atmosphere through anthropogenic and natural mechanisms. These sources have signatures in the aerosol optical and microphysical properties that can be used to identify the aerosol type/mixture. Spectral aerosol absorption information (absorption Angstrom exponent; AAE) used in conjunction with the particle size parameterization (extinction Angstrom exponent; EAE) can only identify the dominant absorbing aerosol type in the sample volume (e.g., black carbon vs. iron oxides in dust). This AAE/EAE relationship can be expanded to also identify non-absorbing aerosol types/mixtures by applying an absorption weighting. This new relationship provides improved aerosol type distinction when the magnitude of absorption is not equal (e.g, black carbon vs. sulfates). The Aerosol Robotic Network (AERONET) data provide spectral aerosol optical depth and single scattering albedo - key parameters used to determine EAE and AAE. The proposed aerosol type/mixture relationship is demonstrated using the long-term data archive acquired at AERONET sites within various source regions. The preliminary analysis has found that dust, sulfate, organic carbon, and black carbon aerosol types/mixtures can be determined from this AAE/EAE relationship when applying the absorption weighting for each available wavelength (Le., 440, 675, 870nm). Large, non-spherical dust particles absorb in the shorter wavelengths and the application of 440nm wavelength absorption weighting produced the best particle type definition. Sulfate particles scatter light efficiently and organic carbon particles are small near the source and aggregate over time to form larger less absorbing particles. Both sulfates and organic carbon showed generally better definition using the 870nm wavelength absorption weighting. Black carbon generation results from varying combustion rates from a number of sources including industrial processes and biomass burning. Cases with primarily black carbon showed improved definition in the 870nm wavelength absorption weighting due to the increased absorption in the near-infrared wavelengths, while the 440nm wavelength provided better definition when black carbon mixed with dust. Utilization of this particle type scheme provides necessary information for remote sensing applications, which needs a priori knowledge of aerosol type to model the retrieved properties especially over semi-bright surfaces. In fact, this analysis reveals that the aerosol types occurred in mixtures with varying magnitudes of absorption and requires the use of more than one assumed aerosol mixture model. Furthermore, this technique will provide the aerosol transport model community a data set for validating aerosol type.

Giles, D. M.↗
NASA NTRS1984

Interplanetary navigation

The evolution of NASA's planetary navigation techniques is traced, and radiometric and optical data types are described. Doppler navigation; the Deep Space Network; differenced two-way range techniques; differential very long base interferometry; and optical navigation are treated. The Doppler system enables a spacecraft in cruise at high absolute declination to be located within a total angular uncertainty of 1/4 microrad. The two-station range measurement provides a 1 microrad backup at low declinations. Optical data locate the spacecraft relative to the target to an angular accuracy of 5 microrad. Earth-based radio navigation and its less accurate but target-relative counterpart, optical navigation, thus form complementary measurement sources, which provide a powerful sensory system to produce high-precision orbit estimates.

Stuart, J. R.↗
NASA NTRS1994

Photonics: From target recognition to lesion detection

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Henry, E. Michael↗