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At least 343 records · Page 19

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗

TESS Data Release Notes:Reprocessing of Sectors 14–19, DR30 & DR33

TESS data release 30 (DR30) provides reprocessed data products of Sector 14 to 19. The updated data products were generated using version 4.0 of the science processing pipeline and conform to the final set of data anomaly flags defined over the last two years of TESS data analysis and pipeline development. Data release 33 (DR33) corresponds to a multisector search for transiting planets in the same reprocessed data. A detailed description of the changes in the data products in DR30 and DR33 is discussed in§2, and a brief list of changes is summarized here: The timestamps for 2 minute cadence and FFI data are more accurate. The differences between reprocessed data and previous data releases are less than 2.0 seconds in all cases. Photometric apertures were increased in size for targets with T mag<11. Three new Data Anomaly Flags were added to mitigate the effects of scattered light:–Cadences with strong scattered light signals or saturation effects that corrupt the calibration data are flagged and removed from analysis (bit 15, value 16384, “Bad Calibration Exclude”).–Scattered light data anomaly flags are customized for each target, and flagged automatically based on the local background level (bit 13, value 4096, ”Scattered light flag”).–Cadences with insufficient targets to derive cotrending basis vectors are flagged and the PDCSAP FLUX light curves are set to NULL at these times (bit 16, value 32768, “Insufficient Targets for Error Correction Exclude”). The planet search of the reprocessed light curves produced a different set of TCEs from the original processed data. Although there is a high degree of overlap between the original and reprocessed data (∼83% of targets produced TCEs in common), new TCEs were produced in DR30 and not every TCE from previous data releases was recovered. The same is true of the multisector search results from DR33 compared to DR28

TESS'↗

Lessons Learned from Large-Scale Aerospace Structural Testing

Large-scale testing of aerospace structures is frequently the final step in a development project to validate the structural performance, and that typically involves a large cost and time investment. In order to ensure that the testing provides the required data, avoiding errors that can result in an unsuccessful test and failure to meet objectives is critical. Presented herein are five lessons learned to provide insight to those conducting tests in order to help them avoid known pitfalls that may result in an unsuccessful test. Five subject large-scale tests are described, and include two composite wing tests, a composite hybrid-wing body center section test, a full-scale 27.5-ft diameter metallic barrel test, and an 8-ft diameter metallic barrel test. Problems identified during the testing and mitigation approaches to solve the problems are presented, then the lessons learned are summarized.

Lessons Learned↗

Lessons Learned from Large-Scale Aerospace Structural Testing

Large-scale testing of aerospace structures is frequently the final step in a development project to validate the structural performance, and that typically involves a large cost and time investment. In order to ensure that the testing provides the required data, avoiding errors that can result in an unsuccessful test and failure to meet objectives is critical. Presented herein are five lessons learned to provide insight to those conducting tests in order to help them avoid known pitfalls that may result in an unsuccessful test. Five subject large-scale tests are described, and include two composite wing tests, a composite hybrid-wing body center section test, a full-scale 27.5-ft diameter metallic barrel test, and an 8-ft diameter metallic barrel test. Problems identified during the testing and mitigation approaches to solve the problems are presented, then the lessons learned are summarized.

Lessons Learned↗

Mitigation of pulsed RFI via automatic gain control

Three automatic gain control (AGC) strategies and their potential capabilities for mitigation of pulsed radio frequency interference (RFI) over a coded, nonlinear channel are examined. The first updates the AGC control voltage once each symbol interval in accordance with a prespecified criterion. The second implementation is designed to first detect high level RFI and then appropriately update its gain. The final implementation is a wideband device which updates its gain once each symbol interval by reducing the gain in direct proportion to a suitable power measurement. Computed results treat pulsed noise and pulsed CW RFI and compare performances in terms of bit error rate (BER) at the output of a Viterbi decoder.

Chang, R. W.-S.↗

Barophysiology and Biophysics

Decompression is an important aspect of extravehicular activity (EVA). Errors can result in decompression sickness (DCS) if the protective measures are too liberal, while valuable on-orbit time is dissipated in prophylactic methodologies that are excessively conservative. Nucleation is an important consideration in many natural events, and its control is very important in many industrial procedures. The amount of Extravehicular Activity (EVA) that will be required during the construction of the International Space Station exceeds all of the other activity combined. The requirements in astronaut time and consumables (breathing oxygen and air) will be considerable. In an attempt to mitigate these requirements, Project ARGO was investigated in 1990 to investigate the effects of gravitational forces on the musculoskeletal system. This work has led to the present plans for the reduction of prebreathe duration. Over the past decade, research has been directed towards an understanding of the biophysical basis of the formation and growth of the decompression gas phase with the goal of improving the efficiency of the EVA process. In the past, we have direct work towards a more complete understanding of gas bubble formation and growth and exercise-enhanced washout during oxygen prebreathe.

Powell, Michael R.↗

Characterizing the Impact of Equatorial Plasma Bubbles on GNSS Accuracy for Crop Yield Estimation in Brazil with NASA GOLD Data

In Brazil, equatorial plasma bubbles are the primary space weather phenomenon impacting the performance of Global Navigation Satellite Systems (GNSS), causing signal disruptions and positional inaccuracies in agricultural machinery used for mapping fields, guiding machinery, and ensuring accurate planting, spraying, and harvesting. As a result, farmers and stakeholders face challenges in maintaining accurate operational capabilities, often needing to shut down machinery to mitigate these effects. This project evaluated the feasibility of using NASA’s Heliophysics observations for a case study in March 2024. Data from NASA's Global-scale Observations of the Limb and Disk (GOLD) instrument were used to characterize equatorial plasma bubbles, while amplitude and phase indices from ground-based GNSS receivers confirmed their presence and impact on signal disruptions. Additionally, data from a local farm's rover receiver assessed the practical implications of these disruptions on Real-Time Kinematic (RTK) GNSS-based operations by calculating the 2-dimensional error. The project involved collaboration across multiple different organizations and sectors, including NASA’s Crustal Dynamics Data Information System (CDDIS) researchers, John Deere, a Brazilian farm for data acquisition, and Brazilian universities for data interpretation. The results aim to inform Brazilian farmers about position errors affecting their precision agriculture operations and provide insights into the needs of space weather data users and modeling. Lessons from this case study will guide future integration of space weather data and modeling with end users.

Melissa Marquez↗

Simulations and Visualizations of Hurricane Sandy (2012) as Revealed by the NASA CAMVis

Storm Sandy first appeared as a tropical storm in the southern Caribbean Sea on Oct. 22, 2012, moved northeastward, turned northwestward, and made landfall near Brigantine, New Jersey in late October. Sandy devastated surrounding areas, caused an estimated damage of $50 billion, and became the second costliest tropical cyclone (TC) in U.S. History surpassed only by Hurricane Katrina (2005). To save lives and mitigate economic damage, a central question to be addressed is to what extent the lead time of severe storm prediction such as Sandy can be extended (e.g., Emanuel 2012; Kerr 2012). In this study, we present 10 numerical experiments initialized at 00 and 1200 UTC Oct. 22-26, 2012, with the NASA coupled advanced global modeling and visualization systems (CAMVis). All of the predictions realistically capture Sandy's movement with the northwestward turn prior to its landfall. However, three experiments (initialized at 0000 UTC Oct. 22 and 24 and 1200 UTC Oct. 22) produce larger errors. Among the 10 experiments, the control run initialized at 0000 UTC Oct. 23 produces a remarkable 7-day forecast. To illustrate the impact of environmental flows on the predictability of Sandy, we produce and discuss four-dimensional (4-D) visualizations with the control run. 4-D visualizations clearly demonstrate the following multiscale processes that led to the sinuous track of Sandy: the initial steering impact of an upper-level trough (appearing over the northwestern Caribbean Sea and Gulf of Mexico), the blocking impact of systems to the northeast of Sandy, and the binary interaction with a mid-latitude, upper-level trough that appeared at 130degrees west longitude on Oct. 23, moved to the East Coast and intensified during the period of Oct. 29-30 prior to Sandy's landfall.

visualizations↗

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗

Root Cause Analysis of the Data Refinement Process – Medical Conditions Capability Resource Tables

The medical system for spaceflight thus far has been designed to support missions in low earth orbit (LEO). Crew capabilities are limited and heavily dependent on the team of medical support staff at Mission Control Center (MCC) to guide diagnosis and management. However, missions to the Moon and Mars will suffer from several constraints that will make this ground support focused approach to care ineffective. In order to update and modify medical system design, NASA has relied on Probabilistic Risk Assessment (PRA) modeling to mitigate medical risk through trade space analysis. Specifically, capability resource tables (CRT’s) were developed to create a dataset of resources required to manage a list of accepted medical conditions significant in exploration spaceflight. With 120 conditions, this dataset contained hundreds of capabilities and thousands of resources with tens of thousands of cells of data. Initially these tables were built in excel for high throughput during development, but ultimately had to be transferred, managed, and modified into the Evidence Library database for modeling purposes. The process of collating and reviewing the Evidence Library revealed numerous errors in the dataset that had to be corrected through iterative changes. Several error types emerged during this process and can be broken into specific classifications defined as “input”, “transcription”, “structural”, “branching”, and “information”. In reviewing these error types through the root cause analysis (RCA) approach, we were able to identify the contributors to these errors which included single data review points, changing product end goals, limited software selection, time constraints and several others. By reviewing and evaluating the underlying causes we can provide possible system improvements that can be implemented for current and future data management in PRA model inputs.

A. Anderson↗

Space Radiation Cancer Risk Projections for Exploration Missions: Uncertainty Reduction and Mitigation

In this paper we discuss expected lifetime excess cancer risks for astronauts returning from exploration class missions. For the first time we make a quantitative assessment of uncertainties in cancer risk projections for space radiation exposures. Late effects from the high charge and energy (HZE) ions present in the galactic cosmic rays including cancer and the poorly understood risks to the central nervous system constitute the major risks. Methods used to project risk in low Earth orbit are seen as highly uncertain for projecting risks on exploration missions because of the limited radiobiology data available for estimating HZE ion risks. Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Monte-Carlo sampling from subjective error distributions represents the lack of knowledge in each factor to quantify risk projection overall uncertainty. Cancer risk analysis is applied to several exploration mission scenarios. At solar minimum, the number of days in space where career risk of less than the limiting 3% excess cancer mortality can be assured at a 95% confidence level is found to be only of the order of 100 days.

Cucinotta, Francis↗

Straight Ahead in Microgravity

This joint ESA-NASA study will address adaptive changes in spatial orientation related to the subjective straight ahead, and the use of a vibrotactile sensory aid to reduce perceptual errors. The study will be conducted before and after long-duration expeditions to the International Space Station (ISS) to examine how spatial processing of target location is altered following exposure to microgravity. This project specifically addresses the sensorimotor research gap "What are the changes in sensorimotor function over the course of a mission?" Six ISS crewmembers will be requested to participate in three preflight sessions (between 120 and 60 days prior to launch) and then three postflight sessions on R+0/1 day, R+4 +/-2 days, and R+8 +/-2 days. The three specific aims include: (a) fixation of actual and imagined target locations at different distances; (b) directed eye and arm movements along different spatial reference frames; and (c) the vestibulo-ocular reflex during translation motion with fixation targets at different distances. These measures will be compared between upright and tilted conditions. Measures will then be compared with and without a vibrotactile sensory aid that indicates how far one has tilted relative to the straight-ahead direction. The flight study was been approved by the medical review boards and will be implemented in the upcoming Informed Crew Briefings to solicit flight subject participation. Preliminary data has been recorded on 6 subjects during parabolic flight to examine the spatial coding of eye movements during roll tilt relative to perceived orientations while free-floating during the microgravity phase of parabolic flight or during head tilt in normal gravity. Binocular videographic recordings obtained in darkness allowed us to quantify the mean deviations in gaze trajectories along both horizontal and vertical coordinates relative to the aircraft and head orientations. During some parabolas, a vibrotactile sensory aid provided feedback of body orientation relative to the plane coordinates. RESULTS Both variability and curvature of gaze trajectories increased during roll tilt compared to the upright position. The saccades were less accurate during parabolic flight compared to measurements obtained in normal gravity. Although subjects were instructed to look off in the distance while performing the eye movements, fixation distance varied with vertical gaze direction independent of whether the saccades were made along perceived aircraft or head orientations. The increased errors in gaze trajectories along both perceived orientations during microgravity can be attributed to the otolith's role in spatial coding of eye movements. A change in an individual's egocentric reference might have negative consequences on evaluating the direction of an approaching object or on the accuracy of reaching movements or locomotion. Consequently, investigating how microgravity affects the target location will have theoretical, operational and even clinical implications for future space exploration missions. The use of vibrotactile feedback as a sensorimotor countermeasure is applicable to balance therapy applications for vestibular loss patients and the elderly to mitigate risks due to loss of orientation.

Wood, S. J.↗

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗

SCREAM: Space-based Cognitive Reliability Error Analysis Method

Given both ground-based performance shaping factors (PSFs) collected by the U.S. Nuclear Regulatory Commission (USNRC) and potential space-based PSFs collected by JSC's HH&P, this year's task is to determine how to combine them for future human reliability analysis (HRA) of space missions. All HRA to date for space missions have been based on ground data (i.e. 1-G environment). There is no space-based HRA approach. The target of this project to produce a "first of its kind" HRA approach for space missions. As humans go beyond Earth orbit and missions become longer, human performance and reliability is expected to degrade. The questions become by how much, when, and what, leading to defining the overall effect on crew risk. Knowing this information earlier rather than later will help us mitigate this risk by vehicle design, crew training, and operational workarounds.

Boyer, Roger L.↗

Response to Comment on 'Prevented Mortality and Greenhouse Gas Emissions from Historical and Projected Nuclear Power'

Sovacool et al.'s analysis of our paper contains numerous errors, misinterpretations, and dubious assumptions. For instance, we make no presumption in our paper that nuclear power is the only major option to replace fossil fuels nor have we in the past, as evidenced by our other peer-reviewed publications. Furthermore, all of our results are based on complete fuel cycle analysis and are presented as mean values along with their ranges. Thus it is incorrect to claim that we single out the worst estimates for coal mortality. Contrary to Sovacool et al.'s assertions, our only bias is our belief that humanity's best chance of success for mitigating the daunting challenge of climate change is to utilize all available and proven means.

coal↗

Radiation Risk Projections for Space Travel

Space travelers are exposed to solar and galactic cosmic rays comprised of protons and heavy ions moving with velocities close to the speed of light. Cosmic ray heavy ions are known to produce more severe types of biomolecular damage in comparison to terrestrial forms of radiation, however the relationship between such damage and disease has not been fully elucidated. On Earth, we are protected from cosmic rays by atmospheric and magnetic shielding, and only the remnants of cosmic rays in the form of ground level muons and other secondary radiations are present. Because human epidemiology data is lacking for cosmic rays, risk projection must rely on theoretical understanding and data from experimental models exposed to space radiation using charged particle accelerators to simulate space radiation. Although the risks of cancer and other late effects from cosmic rays are currently believed to present a severe challenge to space travel, this challenge is centered on our lack of confidence in risk projections methodologies. We review biophysics and radiobiology data on the effects of the cosmic ray heavy ions, and the current methods used to project radiation risks . Cancer risk projections are described as a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Risk projections for space travel are described using Monte-Carlo sampling from subjective error di stributions that represent the lack of knowledge in each factor that contributes to the projection model in order to quantify the overall uncertainty in risk projections. This analysis is applied to space mi ssion scenarios including lunar colony, deep space outpost, and a Mars mission. Results suggest that the number of days in space where cancer mortality risks can be assured at a 95% confidence level to be below the maximum acceptable risk for radi ation workers on Earth or the International Space Station is only on the order of 100-200 days. Approaches to reduce these unceI1ainties and mitigate risks are described.

Cucinotta, Francis↗

Charged Particle Dynamics in the Lunar Environment

As the Artemis Program streams forward, organizations of scientists and engineers across the country have been coming together to solve the complex network of problems to once again achieve the milestone of successfully touching down on the moon. This project is no exception, and it has been an honor to work with the Electrostatics and Surface Physics Laboratory (ESPL), a lab within the Exploration Research and Technology Programs’ Spaceport Technologies Office (UB-G) located at the National Aeronautics and Space Administration at Kennedy Space Center (NASA KSC). The authors and their mentor James R. Phillips III3, in tandem with researchers from the Astrodynamics and Space Robotics Laboratory (ASRL) at the University of Central Florida (UCF), have been working on creating a state-of-the-art (SOA) granular gas dynamics model for particulate contamination prevention and mitigation purposes. In essence, the underlying objective for this project is to more accurately model the resulting electrodynamic interactions between lunar regolith grains with applications to dust mitigation and rocket engine plume surface interactions. To achieve this goal, the team has been expanding upon existing open source classical molecular dynamics code developed by Sandia National Laboratories (SNL). The following reports on the details of the problem at hand as well as the contributions that the authors have made towards resolution, including but not limited to the encoding of physical attributes and interactions for non-spherical polydisperse particle distributions within various bed geometries and preemptive data analysis implementations. Significant data analysis processes were utilized, and several original algorithms were created to perform critical evaluations, resulting in only a 0.006% error in discrepancy.

Annelisa B Esparza↗