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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Online Simulation of Radiation Track Structure Project

Space radiation comprises protons, helium and high charged and energy (HZE) particles. High-energy particles are a concern for human space flight, because they are no known options for shielding astronauts from them. When these ions interact with matter, they damage molecules and create radiolytic species. The pattern of energy deposition and positions of the radiolytic species, called radiation track structure, is highly dependent on the charge and energy of the ion. The radiolytic species damage biological molecules, which may lead to several long-term health effects such as cancer. Because of the importance of heavy ions, the radiation community is very interested in the interaction of HZE particles with DNA, notably with regards to the track structure. A desktop program named RITRACKS was developed to simulate radiation track structure. The goal of this project is to create a web interface to allow registered internal users to use RITRACKS remotely.

Plante, Ianik↗
NASA NTRS2014

Upgrade of the NASA 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) to its Full Science Capability of Sun-Sky-Cloud-Trace Gas Spectrometry in Airborne Science Deployments

The objectives of this task in the AITT (Airborne Instrument Technology Transition) Program are to (1) upgrade the NASA 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument to its full science capability of measuring (a) direct-beam sun transmission to derive aerosol optical depth spectra, (b) sky radiance vs scattering angle to retrieve aerosol absorption and type (via complex refractive index spectra, shape, and mode-resolved size distribution), (c) zenith radiance for cloud properties, and (d) hyperspectral signals for trace gas retrievals, and (2) demonstrate its suitability for deployment in challenging NASA airborne multiinstrument campaigns. 4STAR combines airborne sun tracking, sky scanning, and zenith pointing with diffraction spectroscopy to improve knowledge of atmospheric constituents and their links to air pollution, radiant energy budgets (hence climate), and remote measurements of Earth's surfaces. Direct beam hyperspectral measurement of optical depth improves retrievals of gas constituents and determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution. 4STAR measurements are intended to tighten the closure between satellite and ground-based measurements. 4STAR incorporates a modular sun-tracking/sky-scanning optical head with fiber optic signal transmission to rack mounted spectrometers, permitting miniaturization of the external optical head, and future detector evolution. 4STAR test flights, as well as science flights in the 2012-13 TCAP (Two-Column Aerosol Project) and 2013 SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) have demonstrated that the following are essential for 4STAR to achieve its full science potential: (1) Calibration stability for both direct-beam irradiance and sky radiance, (2) Improved light collection and usage, and (3) Improved flight operability and reliability. A particular challenge for the AITT-4STAR project has been conducting it simultaneously with preparations for, and execution of, ARISE (Arctic Radiation - IceBridge Sea&Ice Experiment), a NASA airborne science deployment (unplanned when AITT-4STAR was selected for funding) in which 4STAR will deploy to Thule, Greenland, and Fairbanks, Alaska, on the NASA C- 130. This presentation describes progress to date in accomplishing AITT-4STAR goals, and plans for project completion.

Sun-Sky-Cloud-Trace↗
NASA NTRS2014

Ground Data System Analysis Tools to Track Flight System State Parameters for the Mars Science Laboratory (MSL) and Beyond

Flight software parameters enable space mission operators fine-tuned control over flight system configurations, enabling rapid and dynamic changes to ongoing science activities in a much more flexible manner than can be accomplished with (otherwise broadly used) configuration file based approaches. The Mars Science Laboratory (MSL), Curiosity, makes extensive use of parameters to support complex, daily activities via commanded changes to said parameters in memory. However, as the loss of Mars Global Surveyor (MGS) in 2006 demonstrated, flight system management by parameters brings with it risks, including the possibility of losing track of the flight system configuration and the threat of invalid command executions. To mitigate this risk a growing number of missions have funded efforts to implement parameter tracking parameter state software tools and services including MSL and the Soil Moisture Active Passive (SMAP) mission. This paper will discuss the engineering challenges and resulting software architecture of MSL's onboard parameter state tracking software and discuss the road forward to make parameter management tools suitable for use on multiple missions.

Allard, Dan↗
NASA NTRS2015

Tracking Three-Dimensional Fish Behavior with a New Marine Acoustic Telemetry System

The persistent monitoring capability provided by acoustic telemetry systems allows us to study behavior, movement, and resource selection of mobile marine animals. Current marine acoustic telemetry systems are challenged by localization errors and limits in the number of animals that can be tracked simultaneously. We designed a new system to provide detection ranges of up to 1 km, to reduce localization errors to less than 1 m, and to increase to 500 the number of unique tags simultaneously tracked. The design builds on HTIs experience of more than a decade developing acoustic telemetry systems for freshwater environments. A field trial of the prototype system was conducted at the University of Washingtons Friday Harbor Marine Laboratory (Friday Harbor, WA). Copper rockfish (Sebastes caurinus) were selected for field trials of this new system because their high site-fidelity and small home ranges provide ample opportunity to track individual fish behavior while testing our ability to characterize the movements of a species of interest to management authorities.

acoustic telemetry↗
NASA NTRS2017

Small Orbital Stereo Tracking Camera Technology Development

Any exploration vehicle assembled or Spacecraft placed in LEO or GTO must pass through this debris cloud and survive. Large cross section, low thrust vehicles will spend more time spiraling out through the cloud and will suffer more impacts.Better knowledge of small debris will improve survival odds. Current estimated Density of debris at various orbital attitudes with notation of recent collisions and resulting spikes. Orbital Debris Tracking and Characterization has now been added to NASA Office of Chief Technologists Technology Development Roadmap in Technology Area 5 (TA5.7)[Orbital Debris Tracking and Characterization] and is a technical gap in the current National Space Situational Awareness necessary to safeguard orbital assets and crews due to the risk of Orbital Debris damage to ISS Exploration vehicles. The Problem: Traditional orbital trackers looking for small, dim orbital derelicts and debris typically will stare at the stars and let any reflected light off the debris integrate in the imager for seconds, thus creating a streak across the image. The Solution: The Small Tracker will see Stars and other celestial objects rise through its Field of View (FOV) at the rotational rate of its orbit, but the glint off of orbital objects will move through the FOV at different rates and directions. Debris on a head-on collision course (or close) will stay in the FOV at 14 Km per sec. The Small Tracker can track at 60 frames per sec allowing up to 30 fixes before a near-miss pass. A Stereo pair of Small Trackers can provide range data within 5-7 Km for better orbit measurements.

Bryan, Tom↗
NASA NTRS2018

NASA Space Network Project Operations Management: Past, Present and Future for the Tracking and Data Relay Satellite Constellation

The NASA Space Network (SN) Operations began with the launch of the first Tracking and Data Relay Satellite (TDRS-1) on April 4, 1983 with on-orbit operations conducted from the White Sands Ground Terminal (WSGT) in Las Cruces, New Mexico. Over the past 35 years, the SN has evolved to its current configuration comprised of four strategically located satellite ground stations and a constellation of ten geosynchronous Tracking and Data Relay Satellites that provide customer support 24 hours a day, 365 days per year, at an unprecedented 99.9% proficiency. The Space Network provides total global Communications, Data Relay, and Tracking services for Low Earth Orbiting (LEO) satellites, Human Space Flight, Expendable Launch Vehicles (ELV) and Scientific missions. This paper will address the Operations Management of the NASA Space Network and the complexities associated with this responsibility, as well as significant mission support highlights.

Sobchak, Ted↗
NASA NTRS2018

Auto Tracking Antenna Platform

The present invention is an auto tracking antenna platform upon which multiple antenna elements can be mounted to track a common moving object. The antenna tracking platform generally comprises a bottom pedestal enclosing a rotary azimuth actuator for controlled-rotary motion about the single vertical (z) axis, and an upper multi-tier framework housing a horizontal antenna-mounting beam pivotally supported for rotation about a horizontal (x) axis, and a drive assembly for direct-drive rotation of the antenna-mounting bar. Antenna elements are mounted along the horizontal mounting bar and the feeds routed through the azimuth actuator. This enables the use of fiber optic rotary joints or slip rings to pass data and video, instead of RF (waveguide) rotary joints which are required to pass high power RF signals.

Sanner, Kurt G↗
NASA NTRS2018

Impairment of Human Ocular Tracking with Low-Dose Alcohol

Previous studies have documented adverse effects of alcohol on oculomotor performance. For example, moderate-dose alcohol (yielding a Blood Alcohol Concentration or BAC of 0.04-0.1%) has been shown to decrease steady-state pursuit gain (Fransson et al., 2010, Clin Neurophysiol, 121(12): 2134; Moser et al., 1998, J Neurol, 245(8): 542; Roche & King, 2010, Psychopharmacology, 212(1): 33), to increase saccade latency (Moser et al., 1998, J Neurol, 245(8): 542; Roche & King, 2010, Psychopharmacology, 212(1): 33), to decrease peak saccadic velocity (Fransson et al., 2010, Clin Neurophysiol, 121(12): 2134; Roche & King, 2010, Psychopharmacology, 212(1): 33), and to increase the frequency of catch-up saccades (Moser et al., 1998, J Neurol, 245(8): 542). Here, we administered two doses of ethanol on different days, yielding moderate (0.06%) and low (0.02%) levels of initial BAC, to examine the effects on human ocular tracking over BACs ranging from 0.00 to 0.07%. Twelve subjects (8 females) participated in a 5-day study. Three days of at-home measurements of daily activity and sleep were monitored, followed by two laboratory days where, ~5 hours after awakening, we administered one of the two possible single doses of alcohol. Using a previously published paradigm (Liston & Stone, 2014, J Vis, 14(14): 12), we measured oculomotor performance multiple times throughout the day with three pre-dosing baseline runs and bi-hourly post-dosing test runs until the subject recorded a BAC of 0.00% for two hours. BAC was measured before each run using an Alco-Sensor IV breathalyzer (Intoximeters, Inc., St. Louis, MO). For each of the oculometric measures, for each subject, we computed the within-subject % deviation for each test run from their baseline averaged across their three pre-dosing runs. We then averaged the data across subjects in 0.01% BAC bins. Finally, we used linear regression to compute the slope and x-intercept (threshold) of the mean binned % deviation as a function of BAC. We found that pursuit initiation was impaired at very low BAC levels, with significant (p < 0.002) linear trends in latency (+1.3%/0.01%BAC) and initial acceleration (-4.6%/0.01%BAC) with extrapolated absolute thresholds at or below 0.01% BAC. We also found that steady-state tracking was impaired showing significant (p < 0.002) linear trends in gain (- 3.8%/0.01%BAC) and catch-up saccade amplitude (+9.1%/0.01%BAC), again with extrapolated absolute thresholds around 0.01% BAC. We also found a significant (p < 0.02) increase in pursuit direction noise (+9.8%/0.01%BAC) with an extrapolated absolute threshold below 0.01% BAC. Many aspects of ocular tracking are impaired in a dose-dependent manner beginning at a BAC level around 0.01%, with significant effects at levels lower than previously reported and up to 8-times lower than the legal limit for driving in most states.

human performance↗
NASA NTRS2018

Analyzing the Relationship between Tracking and Covariance for Satellite Collision Avoidance

This presentation will display statistical analysis performed with over 150,000 Conjunction Data Messages (CDMs) received for the Earth Observing System (EOS) Aqua, Aura and Terra satellites within the three year period of March 2015 through February 2018. The analysis performed demonstrates the relationship between the covariance of a secondary object and the amount of tracks it receives, as a function of Time to Closest Approach (TCA). The examination indicates that higher tracking frequencies result in lower uncertainties inclusively from the time the data is screened up until TCA. Further investigation displays the impacts of how additional observations of secondary objects lower their position uncertainties and what period of time prior to TCA convergence of the covariance can be expected depending on how well the objects are tracked. Data points from several recent EOS High Interest Events (HIEs) are used to exemplify this analysis.

Collision Avoidance↗
NASA NTRS2019

The Solar Neutron TRACking (SONTRAC) Instrument for the Detection of Fast Neutrons

The detection of fast neutrons has important applications in several fields including solar, Geospace and planetary physics. Neutrons are challenging to detect and measurements of them typically suffer from high background rates. High-energy neutrons (>50 MeV) pose even more challenges, because the traditional double-scatter technique based on a time-of-flight (ToF) measurement is limited by short flight paths and small detector sizes characteristic of small satellite platforms. It is now possible to perform high-energy neutron measurements inside a large monolithic detector by imaging the recoil proton tracks, thus eliminating the need for a measure of the time-of-flight. The concept is based on a spectrometer assembled from numerous thin hydrogenous scintillating fibers that allow ionization track imaging. Fine grained readout is now possible with arrays of1-mm pitch silicon photomultipliers (SiPMs). The Solar Neutron TRACking (SONTRAC) instrument, equipped with scintillating fibers readout with SiPMs sensors, provides high-resolution, fine grained, imaging of fast (between 20-200 MeV) neutron scatters in a compact, low-power design ideal for small satellite(and aircraft) platforms. We discuss below applications of this technology and performance characteristics of the prototype SONTRAC instrument.

de Nolfo, Georgia A.↗
NASA NTRS2020

Customer Avionics Interface Development and Analysis Development Activity Tracking System

The Customer Avionics Interface Development and Analysis (CAIDA) Development Activity (DA)Tracking System is a Microsoft Access Database that tracks, organizes, and analyzes data about DAs from the work management tool. The CAIDA DA Tracking System takes data imported from the work management system. Once in the system, the data is filtered to generate each DA’s Asset. From there, many different queries are run on the data and their results are imported into forms to create graphs to get and display a wide range of metrics. These graphs are automatically updated with each new data import and over time. They can be easily exported for use in presentations, documents, etc. Additionally, the system is highly customizable and can be added upon to include more data members, generate new graphs, and much more.

Tara Conti↗
NASA NTRS2018

Towards a Unified View of Modeling and Programming (ISoLA 2018 Track Introduction)

The article provides an introduction to the track: Towards a Unified View of Modeling and Programming, organized by the authors of this paper as part of ISoLA 2018: the 8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation. A total of 19 researchers were invited to present their views on the two questions: what are the commonalities between modeling and programming languages, and should we strive towards a unified view of modeling and programming? The idea behind the track, which is a continuation of a similar track at ISoLA 2016, emerged as a result of experiences gathered in the three fields: formal methods, model-based software engineering, and programming languages, and from the observation that these technologies share a large common part, to the extent where one may ask, does the following equation hold: modeling = programming?

Steffen, Bernhard↗
NASA NTRS2018

Synthetic Tracking on a Small Telescope

Synthetic tracking uses high speed (up to 10 Hz) low noise (<2e-) large format sensors ~16 Mpix along with a multi-vector shift/add algorithm that coadds multiple image frames to increase the signal to noise ratio (SNR) needed to detect (if present) multiple moving objects in the field of view (FOV). We published the application of synthetic tracking to look for asteroids in 2014 (Shao 2014), but recently have applied it more as well to Earth orbiting objects. We have begun testing the data processing graphical processing unit (GPU) array with a small telescope, a 28 cm Celestron RASA telescope and a low cost low noise 16 Mpix CMOS camera at a dark site in California. This system is now operational with a 2 sqdeg FOV and a limiting magnitude between ~16-17.5 stellar magnitudes (mag) depending on a number of observational parameters for short integration times. The instrument can be used to search for NEOs, where we use much longer integration times to get sensitivity ~ 20.5 mag (at new moon). Synthetic tracking provides significant improvements in both sensitivity and astrometric accuracy.

Turyshev, Slava G.↗
NASA NTRS2021

Detection and Tracking of Aircraft in the Far-Field from Small Unmanned Aerial Systems

Onboard far-field aircraft detection is needed for safe non-cooperative traffic mitigation in autonomous small Unmanned Aerial System (sUAS) operations. Machine vision systems, based on standard optics and visible light detectors, possess the ideal size, weight, and power (SWaP) requirements for sUAS. This work presents the design and analysis of a novel aircraft detection and tracking pipeline based on optical sensing alone. Key contributions of the work include a refined range inequality model based on sensing and detection with FAA well-clear separation assurance distances between aircraft in mind, a detector fusion method to maximize the benefit of two image detectors, and a comparative analysis of Linear Kalman-filtering and Extended Kalman-filtering to seek optimal tracking performance. The pipeline is evaluated offline against multiple intruder platforms, using two types of flight encounters: multirotor sUAS vs. fixed-wing sUAS and multirotor sUAS vs. general aviation(GA)plane. Analysis is restricted to the rate-limiting head-on and departing collision volume cases vertically separated for safety. Results indicate that it is feasible to use the proposed optical spatial-temporal tracking algorithm to provide adequate alerting time to prevent penetration of well-clear separation volumes for both sUAS and GA aircraft.

Unmanned Aerial System↗
NASA NTRS2020

Lunar Magnetic Field Models From Lunar Prospector and SELENE/Kaguya Along-Track Magnetic Field Gradients

We use L1-norm model regularization of |Br| component at the surface on magnetic monopoles bases and along-track magnetic field differences alone (without vector observations) to derive high quality global magnetic field models at the surface of the Moon. The practical advantages to this strategy are the following: monopoles are more stable at closer spacing in comparison to dipoles, improving spatial resolution; L1-norm model regularization leads to sparse models which may be appropriate for the Moon which has regions of localized magnetic field features; and along-track differences reduce the need for ad-hoc external field noise reduction strategies. We examine also the use of Lunar Prospector and SELENE/Kaguya magnetometer data, combined and separately, and find that the Lunar Prospector along-track vector field differences lead to surface field models that require weaker regularization and, hence, result in higher spatial resolution. Significantly higher spatial resolution (wavelengths of roughly 25–30 km) and higher amplitude surface magnetic fields can be derived over localized regions of high amplitude anomalies (due to their higher signal-to-noise ratio). These high-resolution field models are also compared with the results of Surface Vector Mapping approach of Tsunakawa et al. (2015, https://doi.org/10.1002/2014JE004785). Finally, the monopoles- as well as dipoles-based patterns of the Serenitatis high amplitude magnetic feature have characteristic textbook patterns of Br and Bθ component fields from a nearly vertically downwardly magnetized source region and it implies that the principal source of the anomaly was formed when the region was much closer to the north magnetic pole of the Moon.

D. Ravat↗
NASA NTRSDate not supplied

Saccade-Pursuit Coordination during Ocular Tracking across Different Impairment Sources

Purpose: Sleep loss and alcohol have been shown to impair smooth pursuit and its underlying visual motion processing in humans. This study examines the saccadic compensation for this poor pursuit. Methods: Using an established behavioral ocular-tracking paradigm (Liston & Stone, 2014, doi:10.1167/14.14.12), we examined the dose-response of ground lost (pursuit deficit integrated across our 300-ms steady-state tracking interval) and ground gained (increased saccadic response harnessed to compensate)across three separate studies – acute low-dose alcohol administration (LDA; n = 16 subjects), acute sleep loss(ASL; n = 12), and chronic sleep restriction (CSR; n = 12). We computed dose-responses as the linear regression slopes of ground lost and gained across treatment dose (% blood alcohol concentration [BAC] or hours awake). For the CSR study, we computed the mean effect for a single dose (5-hours nightly sleep for 1week). Results: For LDA, there was significantly increased ground lost (P < 0.001) and gained (P < 0.001) with increased %BAC. In addition, the dose-responses were not significantly different (P = 0.35), indicating effectively complete saccadic compensation due to significant increases in both saccadic rate (P < 0.05) and amplitude (P < 0.001). For ASL, there was significantly increased ground lost with time awake (P < 0.01),however ground gained was significantly lower (P < 0.001), indicating, at best, incomplete compensation due to a significant increase in saccadic rate (P < 0.001) but not amplitude (P = 0.10). With CSR, pursuit was again significantly impaired (P < 0.05), with saccadic rate significantly increased (P < 0.05) but, surprisingly, amplitude was significantly decreased (P < 0.05), effectively eliminating ground gained (P = 0.90). Conclusions: Our analyses show that LDA, ASL, and CSR affect tracking differently, suggesting the involvement of different brain pathways. With LDA, the effect appears largely due to the cortical impairment of visual motion processing with largely healthy brainstem and mid-brain responses (driving effective saccadic compensation). ASL and CSR however appear to affect both cortical and sub-cortical pathways, with at best partial saccadic compensation. Lastly, CSR is associated with an additional compromise due to a maladaptive decrease in saccade amplitude.

saccade↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
NASA NTRSDate not supplied

Development and Application of NASA SPoRT’s DustTracker-AI Model for Real-Time Identification and Tracking of Dust in Geostationary Satellite Imagery

The NASA Short-term Prediction Research and Transition (SPoRT) Center developed the DustTracker-AI model for identifying and tracking dust in NASA/NOAA Geostationary Operational Environmental Satellite (GOES) imagery in a real-time framework. A training dataset consisting of day and night dust cases was gathered over the southwestern consisting of 115 distinct images and over a million dust pixels and 256 million no dust pixels. The dataset was separated into training (60%), testing (20%), and validation (20%). A simple random forest machine learning model was developed originally to overcome the problem of night-time dust detection and has been expanded to a comprehensive day/night model for dust identification and tracking. This physically-based machine-learning approach uses NASA/NOAA GOES-16 Advanced Baseline Imager infrared imagery as inputs to the model. The model probability of dust output achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels for all dust images in the validation data set. In conjunction with developing the machine-learning model, the NASA Short-term Prediction Research and Transition Center (SPoRT) partnered with NOAA National Weather Service forecast offices to evaluate the model for utility in weather forecasting operations during the 2021 and 2023 late winter-spring seasons. Preliminary evaluation has indicated the majority of forecasters described the DustTracker-AI probabilities as having added confidence to interpreting the Dust RGB and other satellite products to objectively assess the dust extent and trends and increased the amount of time the dust plume could be tracked into the night as compared to use of the Dust RGB. More recently, SPoRT tested small scale events associated with thunderstorm outflow and burn scars to determine the model’s ability to capture local events. This presentation highlights design of the model, validation/evaluation of model performance, and example cases collected during end user product assessments.

Connor H Welch↗