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At least 721 records · Page 40

Feasibility of NASA TT&C via Commercial Satellite Services

This report presents the results of a study to identify impact and driving requirements by implementing commercial satellite communications service into traditional National Aeronautics and Space Administration (NASA) space-ground communications. The NASA communication system is used to relay spacecraft and instrument commands, telemetry and science data. NASA's goal is to lower the cost of operation and increase the flexibility of spacecraft operations. Use of a commercial network offers the opportunity to contact a spacecraft on a nearly "on-demand" basis with ordinary phone calls to enable real time interaction with science events.

Mitchell, Carl W.↗

Tectonics of the Outer Planet Satellites

Tectonic features on the satellites of the outer planets range from the familiar, such as clearly recognizable graben on many satellites, to the bizarre, such as the ubiquitous double ridges on Europa, the twisting sets of ridges on Triton, or the isolated giant mountains rising from Io's surface. All of the large and middle-sized outer planet satellites except Io are dominated by water ice near their surfaces. Though ice is a brittle material at the cold temperatures found in the outer solar system, the amount of energy it takes to bring it close to its melting point is lower than for a rocky body. Therefore, some unique features of icy satellite tectonics may be influenced by a near-surface ductile layer beneath the brittle surface material, and several of the icy satellites may possess subsurface oceans. Sources of stress to drive tectonism are commonly dominated by the tides that deform these satellites as they orbit their primary giant planets. On several satellites, the observed tectonic features may be the result of changes in their tidal figures, or motions of their solid surfaces with respect to their tidal figures. Other driving mechanisms for tectonics include volume changes due to ice or water phase changes in the interior, thermoelastic stress, deformation of the surface above rising diapirs of warm ice, and motion of subsurface material toward large impact basins as they fill in and relax. Most satellites exhibit evidence for extensional deformation, and some exhibit strike-slip faulting, whereas contractional tectonism appears to be rare. Io s surface is unique, exhibiting huge isolated mountains that may be blocks of crust tilting and foundering into the rapidly emptying interior as the surface is constantly buried by deposits from hyperactive volcanoes. Of the satellites, diminutive Enceladus is spectacularly active; its south polar terrain is a site of young tectonism, copious heat flow, and tall plumes venting into space. Europa's surface is pervasively tectonized, covered with a diverse array of exotic and incompletely understood tectonic features. The paucity of impact craters on Europa suggests that its tectonic activity is ongoing. Geysers on Triton show that some degree of current activity, while tectonic features that cross sparsely cratered terrain indicate that it may also be tectonically active. Ganymede and Miranda both exhibit ancient terrains that have been pulled apart by normal faulting. On Ganymede these faults form a global network, while they are confined to regional provinces on Miranda. Ariel, Dione, Tethys, Rhea, and Titania all have systems of normal faults cutting across their surfaces, though the rifting is less pronounced than it is on Ganymede and Miranda. Iapetus exhibits a giant equatorial ridge that has defied simple explanation. The rest of the large and middle-sized satellites show very little evidence for tectonic features on their surfaces, though the exploration of Titan's surface has just begun.

McKinnon, W. B.↗

Using Reinforcement Learning to Design Missed Thrust Resilient Trajectories

From ion thrusters to solar sails, spacecraft continue to adopt new and more efficient forms of propulsion. As these low-thrust propulsion meth- ods have become more prevalent, new challenges have arisen. Depending on the mission, low-thrust propulsion elements may need to thrust con- tinuously for days/months. During these thrusting periods, external fac- tors, such as a micro-meteoroid impact or a software glitch, may cause the spacecraft to prematurely cease its thrust stage. Half of all deep space missions enter a safe mode where they cannot thrust every four months. These missed thrust events can result in the complete loss of a space- craft for time-dependent trajectories like planetary rendezvous. This paper demonstrates how neural networks, trained using reinforcement learning, can autonomously correct for missed thrust events during an interplanetary trajectory.

Laipert, Frank E.↗

Observation Denial and Performance of a Local Mesoscale Model

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and the CCAFS (XMR) daily rawinsonde observations (RAOB) to issue and verify wind advisories and warnings for operations. These observations are also used by the Spaceflight Meteorology Group (SMG) in Houston, Texas and the Melbourne, Florida National Weather Service office to initialize their locally run mesoscale models. SMG also uses the observations to support shuttle landings at the KSC Shuttie Landing Facility. Due to impending budget cuts, some or all of the KSC/CCAFS wind towers on the east-central Florida mainland and the XMR RAOBs may be eliminated. The loss of these data may impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct a modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (NRF) model initialized with and without KSC/CCAFS wind tower and XMR RAOB observations. The AMU assessed the accuracy of model output by comparing peak wind forecasts with operationally significant wind advisory and warning criteria forecast by the 45 WS. To assess model performance when initialized with and without some of the wind tower and XMR RAOB observations, the AMU conducted a subjective analysis by displaying model wind forecasts graphically with the observations overlaid for comparison and they conducted an objective analysis by comparing the maximum peak wind forecast to the maximum peak wind observed within the KSC/CCAFS wind tower network. Data were collected for twelve warm season cases and eight cool season cases from June - September 2007 and November - January 2008, respectively. For each case chosen, the 45 WS must have issued a wind advisory or warning for the KSC/CCAFS area and the KSC/CCAFS wind towers must have recorded significant wind events, or winds greater than 18 kt.

Watson, Leela R.↗

An exploratory study to determine the integrated technological air transportation system ground requirements of liquid-hydrogen-fueled subsonic, long-haul civil air transports

An exploratory study was conducted to evaluate the feasibility and cost impact of implementing a liquid-hydrogen-fueled (LHz), air transport support system at Chicago-O’Hare International Airport. The study assumed an available supply of hydrogen to the airport boundary. It also assumed that the present widebody fleet at O’Hare was replaced by 400 passenger, LH2-fueled aircraft operating on the current frequency schedule and route network. The LH2 aircraft configurations used in this study were developed during a previous NASA-sponsored study. A baseline air terminal concept was developed which permitted airlines and the airport to operate JP- or LH2-fueled aircraft at common terminal gates. The concept included installation of a hydrogen liquefaction and storage facility on airport property, as well as the fuel distribution system. The capital investment and hydrogen-related operating costs to the airlines were estimated. The study concluded that the system would be technically and operationally feasible at O’Hare, and that economics would be a prime factor in future decisions regarding the use of LH2 as an air transport fuel. Research and technology recommendations were made to improve component efficiency/reliability. The study also concluded that additional investigation should be conducted on the implementation of a nationwide or worldwide LH2 air transportation system, to understand fully the operational and economic implications of the total system, before decisions could be made relative to committing to this option.

Hydrogen↗

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Ichoku, Charles↗

VLBI2010: An Overview

The first concrete actions toward a next generation system for geodetic VLBI began in 2003 when the IVS initiated Working Group 3 to investigate requirements for a new system. The working group set out ambitious performance goals and sketched out initial recommendations for the system. Starting in 2006, developments continued under the leadership of the VLBI2010 Committee (V2C) in two main areas: Monte Carlo simulators were developed to evaluate proposed system changes according to their impact on IVS final products, and a proof-of-concept effort sponsored by NASA was initiated to develop next generation systems and verify the concepts behind VLBI2010. In 2009, the V2C produced a progress report that summarized the conclusions of the Monte Carlo work and outlined recommendations for the next generation system in terms of systems, analysis, operations, and network configuration. At the time of writing: two complete VLBI2010 signal paths have been completed and data is being produced; a number of VLBI2010 antenna projects are under way; and a VLBI2010 Project Executive Group (V2PEG) has been initiated to provide strategic leadership.

Petrachenko, Bill↗

Wallops Ship Surveillance System

Approved as a Wallops control center backup system, the Wallops Ship Surveillance Software is a day-of-launch risk analysis tool for spaceport activities. The system calculates impact probabilities and displays ship locations relative to boundary lines. It enables rapid analysis of possible flight paths to preclude the need to cancel launches and allow execution of launches in a timely manner. Its design is based on low-cost, large-customer- base elements including personal computers, the Windows operating system, C/C++ object-oriented software, and network interfaces. In conformance with the NASA software safety standard, the system is designed to ensure that it does not falsely report a safe-for-launch condition. To improve the current ship surveillance method, the system is designed to prevent delay of launch under a safe-for-launch condition. A single workstation is designated the controller of the official ship information and the official risk analysis. Copies of this information are shared with other networked workstations. The program design is divided into five subsystems areas: 1. Communication Link -- threads that control the networking of workstations; 2. Contact List -- a thread that controls a list of protected item (ocean vessel) information; 3. Hazard List -- threads that control a list of hazardous item (debris) information and associated risk calculation information; 4. Display -- threads that control operator inputs and screen display outputs; and 5. Archive -- a thread that controls archive file read and write access. Currently, most of the hazard list thread and parts of other threads are being reused as part of a new ship surveillance system, under the SureTrak project.

Smith, Donna C.↗

Toward a Coherent Detailed Evaluation of Aerosol Data Products from Multiple Satellite Sensors

Atmospheric aerosols represent one of the greatest uncertainties in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood, there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource, an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, TerraMISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MA~SS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Ichoku, Charles↗

Satellite-Derived Imagery and Transfer Learning: A Novel Technique for Land Cover Classification

Land cover classification is a continuing research topic due to its relevance to land use and land cover changes from impacts such as climate change, agriculture, urbanization, and hazardous weather. Simple access to frequently changing land cover classifications could provide knowledge and decision support to various researchers and agencies across the globe for each of above-mentioned and related influences. This research aims to provide a novel technique for land cover classification of remote sensing imagery; harnessing Artificial Neural Networks and transfer learning (TL). Knowledge sharing techniques within machine learning are typically utilized when training datasets are sparse or transitions between data modalities is required. In this case, two data modalities, multi and hyperspectral data, are considered for knowledge transfer. The large number of continuous spectral bands available from hyperspectral sensors typically provide increased sophisticated land classification capability compared to more traditional multispectral imagery with limited discrete spectral bands. However, large-scale, frequent access to hyperspectral imagery is relatively limited. The proposed classification technique would therefore prove useful in regions in which hyperspectral data are not readily available for classification but multispectral data are. Image segmentation models are trained on each multi and hyperspectral datasets. Knowledge sharing techniques are then applied to each model to understand what knowledge, if any, is gained when moving between the data modalities. The datasets utilized for training and testing a U-Net model include the European Space Agency’s multispectral imager Sentinel-2 and the hyperspectral German Aerospace Center’s Earth Sensing Imaging Spectrometer (DESIS). Initially, only two classes, land and water, are classified for simplicity. However, more complex classes can be added if knowledge sharing is successful. The workflow for image classification through supervised image segmentation with a U-Net model will be discussed along with metrics calculated before and after TL for both Sentinel-2 and DESIS data are applied. Additionally, future steps to advance the sophistication of this technique as well as other applicable methodologies will be explored.

Emily Foshee↗

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗

Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network

The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET.

GOCI↗

Fuzzy set methods for object recognition in space applications

Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

Keller, James M.↗

Sleuthing the MSL EDL Performance from an X Band Carrier Perspective

During the Entry, Descent, and Landing (EDL) of NASA's Mars Science Laboratory (MSL), or Curiosity, rover to Gale Crater on Mars on August 6, 2012 UTC, the rover transmitted an X-band signal composed of carrier and tone frequencies and a UHF signal modulated with an 8kbps data stream. During EDL, the spacecraft's orientation is determined by its guidance and mechanical subsystems to ensure that the vehicle land safely at its destination. Although orientation to maximize telecom performance is not possible, antennas are especially designed and mounted to provide the best possible line of sight to Earth and to the Mars orbiters supporting MSL's landing. The tones and data transmitted over these links are selected carefully to reflect the most essential parameters of the vehicle's state and the performance of the EDL subsystems for post-EDL reconstruction should no further data transmission from the vehicle be possible. This paper addresses the configuration of the X band receive system used at NASA / JPL's Deep Space Network (DSN) to capture the signal spectrum of MSL's X band carrier and tone signal, examines the MSL vehicle state information obtained from the X band carrier signal only and contrasts the Doppler-derived information against the post-EDL known vehicle state. The paper begins with a description of the MSL EDL sequence of events and discusses the impact of the EDL maneuvers such as guided entry, parachute deploy, and powered descent on the frequency observables expected at the DSN. The range of Doppler dynamics possible is derived from extensive 6 Degrees-Of-Freedom (6 DOF) vehicle state calculations performed by MSL's EDL simulation team. The configuration of the DSN's receive system, using the Radio Science Receivers (RSR) to perform open-loop recording for both for nominal and off-nominal EDL scenarios, is detailed. Expected signal carrier power-to-noise levels during EDL are shown and their impact on signal detection is considered. Particular attention is given to the selection of the appropriate RSR processing bandwidths and to its configuration for real-time signal detection. The X-band carrier frequency obtained through post-processing of the open-loop recorded spectrum is given. Detection of spacecraft status and completion of key vehicle events through their Doppler signature is discussed and illustrated. This Doppler-derived information is compared against the very accurate vehicle data obtained post-EDL via MSL's UHF radio subsystem. The paper concludes with a discussion on the advantages and disadvantages of transmitting the X-band carrier and tone signal in the general context of EDL communications and lessons learned for future missions with EDL sequences are given

Mars Science Laboratory (MSL)↗

Mitigating the Impacts of Measurement Error in the Quesst Mission Community Noise Study

Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.

measurement error↗

Long-range Transport of Asian Dust Storms: A Satellite/Surface Perspective on Societal and Scientific Influence

Among the many components contributing to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative forcing effect on the weather/climate system. As much as one-third to half of the global dust emissions, estimated about 800 Tg, are introduced annually into Earth's atmosphere from various deserts in China. Asian dust storm outbreaks are believed to have persisted for hundreds and thousands years over the vast territory of north and northwest China, but not until recent decades that many studies reveal the compelling evidence in recognizing the importance of these eolian dust particles for forming Chinese Loess Plateau and for biogeochemical cycling in the North Pacific Ocean to as far as in the Greenland ice-sheets through long-range transport. The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites and its evolution monitored by satellite and surface network. In this paper, we will demonstrate the capability of a new satellite algorithm, called Deep Blue, to retrieve aerosol properties, particularly but not limited to, over bright-reflecting surfaces such as urban areas and deserts. Recently, many field campaigns were designed and executed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. We will provide an overview of the outbreak of Asian dust storms, near source/sink and their evolution along transport pathway, from space and surface observations. The climatic effects and societal impacts of the Asian dusts will be addressed in depth. (to be presented in the International Workshop on Semi-Arid Land Surface-

Source record↗

Assessment of satellite communications quality study. Addendum 1: Impact of propagation delay on data transmission

The single factor that irrevocably distinguishes geostationary satellite telephony transmission from terrestrial transmission is the greater propagation delay over satellite links. This difference has always provoked vigorous debate over the impact of delay on the subscribers using services incorporating satellite links. The issue is addressed from a variety of directions including human factors studies, laboratory subjective tests that evaluate delay with and without echo, and field tests that obtain data on the opinion of subscribers regarding the quality of service of operational circuits in both national U.S. domestic and international trans-Atlantic network. The tests involved the use of both echo suppressors and echo cancellers.

Campanella, S. J.↗

Performance of a Local Mesoscale Model with Data Denial

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and daily rawinsonde observations (RAOB) to issue and verify wind advisories, watches, and warnings for operations. They are also used by the Spaceflight Meteorology Group and Melbourne, Florida National Weather Service to initialize locally run mesoscale models. Due to impending budget cuts, some or all of the mainland wind towers and RAOBs may be eliminated, The loss of these data may significantly impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct an objective independent modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (WRF) model run with and without KSC/CCAFS wind tower and CCAFS RAOB observations and assessed the accuracy of model forecasts by comparing them to the observations.

Watson, Leela↗