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NASA NTRS2021

Precipitation Retrievals from Passive Microwave Cross-Track Sensors: The Precipitation Retrieval and Profiling Scheme

The retrieval of precipitation (snowfall and rainfall) from satellite sensors on a global basis is essential in aiding our knowledge and understanding of the Earth System and to many societal applications. Measurements from surface-based instruments are essentially limited to populated regions, necessitating the use of satellite-based observations to provide estimates of precipitation across the whole of the Earth’s surface. The temporal and spatial variability of precipitation requires adequate sampling, especially at finer resolutions. It is therefore necessary to exploit all available data from precipitation-capable satellites to ensure the proper representation of precipitation. To date, the estimation of precipitation using passive microwave observations has been largely concentrated upon the conically-scanning imaging instruments, with relatively few techniques exploiting the observations made from the cross-track sounders. This paper describes the development of the Precipitation Retrieval and Profiling Scheme (PRPS) to retrieve precipitation from cross-track sensors, together with its performance against surface radar data and other satellite precipitation retrievals.

Chris Kidd↗

NASA NTRSDate not supplied

Extending the Life of NASA’s Tracking and Data Relay Satellite (TDRS)-8: TDRS-8 Power Challenges And Planning for End of Mission

The United States National Aeronautics and Space Administration (NASA) Near Space Network’s Space Relay (SR) System provides communication relay services to a number of scientific and manned space missions with its Tracking and Data Relay Satellite (TDRS) constellation. NASA’s eighth Tracking and Data Relay Satellite (TDRS) has been experiencing a decline in the health of its power subsystem, and recent reliability analyses indicate that the end of its mission serving the Space Relay is imminent. Launched in 2000, TDRS-8 is the oldest TDRS built upon a Boeing 601 platform, and as such it is the first TDRS to experience these age-related failures. The most prevalent elements of the power subsystem to decline are the solar array circuitry and the Bus Voltage Limiters (BVLs), which prevent too much power from the solar arrays being transferred to the bus by shunting excess current. This means that while the loss of solar array circuits introduces concerns that the solar arrays will continue providing the spacecraft with enough current to remain power positive, the loss of BVLs introduces a concern that the bus may not be adequately protected from overvoltage events. Spacecraft engineers at the TDRS primary ground terminal, the White Sands Complex (WSC) in Las Cruces, New Mexico, and at NASA's Goddard Space Flight Center (GSFC) have also been working in collaboration with Boeing to develop innovative techniques to extend the serviceable life of TDRS-8.

tdrs↗

NASA NTRSDate not supplied

Ground to Air Testing of a Fused Optical-Radar Aircraft Detection and Tracking System

Onboard detection and tracking capability are integral to the sensing component in collision avoidance systems needed to safely operate autonomous urban air taxis and small Unmanned Aircraft Systems. Ground-based validation of detection and tracking systems is an important milestone towards the end goal of real-time collision avoidance using onboard sensors and algorithms. In this work, we evaluate three Extended Kalman Filter(EKF)based fusion trackers with radar and vision detection inputs, and compare them with baseline trackers for each sensor type. Performance is assessed using field collected data of ground to air test flights with the sensors co-located on a stable platform with an instrumented multirotor acting as the intruder performing a waypoint pattern at a distance of1.1km to 0.3km to simulate a head-on collision geometry. Fusing an image-based morphological detector with a radar detector using an EKF covered 74% of the ground truth position updates logged by the flight controller on the multirotor within 50 meters after accounting for alignment offsets while covering 15% more ground truth updates relative to radar only. Removing timestamps when the intruder aircraft is occluded by trees and only considering timestamps where the radar has an update, the EKF image-based morphological detector combined with the radar detector covered 90% of the of the ground truth position updates within 50metersand 97% within 100 meters.

Chester V Dolph↗

NASA NTRSDate not supplied

Terminal Tracking for the Lucy Trojan Asteroid Mission

The most recent NASA Discovery class mission to fly is the Lucy mission to the Trojan Asteroids of Jupiter. Launched in October of 2021, Lucy’s destination will be the unexplored Jupiter Trojan Asteroids that orbit the Sun at the stable L4 and L5 points ahead of, and behind Jupiter. This 12-yearmission will perform close flybys of 1 main belt asteroid, Donaldjohanson, and 7 Trojans asteroids: Eurybates and its satellite Queta, Polymele, Leucus, Orus, and the near equal mass Trojan binary pair, Patroclus andMenoetius. The large distance from earth for the encounters, the high relative velocities and sun incidence angles on approach,and the limited number of Earth observations of the Trojans,make the delivery knowledge highly uncertain. To reduce the delivery uncertainties and maximize science return, Lucy employs a Terminal Tracking System consisting of optical imaging, centroiding and state estimation of the Trojan asteroids on approach and through close approach. This paper presents the Lucy Terminal Tracking System implementation, a brief overview of the mission and the GN&C subsystem.

Philip G Good↗

NASA NTRS2022

Assimilation of Sea Ice Thickness Derived from Cryosat-2 Along-Track Freeboard Measurements into the Met Office's Forecast Ocean Assimilation Model (FOAM)

The feasibility of assimilating sea ice thickness (SIT) observations derived from CryoSat-2 along-track measurements of sea ice freeboard is successfully demonstrated using a 3D-Var assimilation scheme, NEMOVAR, within the Met Office's global, coupled ocean–sea-ice model, Forecast Ocean Assimilation Model (FOAM). The CryoSat-2 Arctic freeboard measurements are produced by the Centre for Polar Observation and Modelling (CPOM) and are converted to SIT within FOAM using modelled snow depth. This is the first time along-track observations of SIT have been used in this way, with other centres assimilating gridded and temporally averaged observations. The assimilation leads to improvements in the SIT analysis and forecast fields generated by FOAM, particularly in the Canadian Arctic. Arctic-wide observation-minus-background assimilation statistics for 2015–2017 show improvements of 0.75 m mean difference and 0.41 m root-mean-square difference (RMSD) in the freeze-up period and 0.46 m mean difference and 0.33 m RMSD in the ice break-up period. Validation of the SIT analysis against independent springtime in situ SIT observations from NASA Operation IceBridge (OIB) shows improvement in the SIT analysis of 0.61 m mean difference (0.42 m RMSD) compared to a control without SIT assimilation. Similar improvements are seen in the FOAM 5 d SIT forecast. Validation of the SIT assimilation with independent Beaufort Gyre Exploration Project (BGEP) sea ice draft observations does not show an improvement, since the assimilated CryoSat-2 observations compare similarly to the model without assimilation in this region. Comparison with airborne electromagnetic induction (Air-EM) combined measurements of SIT and snow depth shows poorer results for the assimilation compared to the control, despite covering similar locations to the OIB and BGEP datasets. This may be evidence of sampling uncertainty in the matchups with the Air-EM validation dataset, owing to the limited number of observations available over the time period of interest. This may also be evidence of noise in the SIT analysis or uncertainties in the modelled snow depth, in the assimilated SIT observations, or in the data used for validation. The SIT analysis could be improved by upgrading the observation uncertainties used in the assimilation. Despite the lack of CryoSat-2 SIT observations available for assimilation over the summer due to the detrimental effect of melt ponds on retrievals, it is shown that the model is able to retain improvements to the SIT field throughout the summer months due to prior, wintertime SIT assimilation. This also results in regional improvements to the July modelled sea ice concentration (SIC) of 5 % RMSD in the European sector, due to slower melt of the thicker sea ice.

Emma K. Fiedler↗

NASA NTRSDate not supplied

Venus Atmospheric Probe and Flyby Relay Spacecraft Cross-Link Tracking Impact on Relative Pointing Accuracy

Scientific exploration of Venus using an atmospheric probe requires relaying telemetry to Earth as the probe descends through the atmosphere to the surface of Venus. Using the flyby spacecraft to relay the probe telemetry to Earth will require precise carrier-to-probe pointing accuracy of the relay spacecraft’s antenna. NASA’s Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission uses this carrier-to-probe relay technique. Although DAVINCI includes a coherent cross-link for science, this is not baselined for navigation tracking. This paper explores the potential effectiveness of cross-link tracking for reducing trajectory uncertainty and improving spacecraft-to-probe pointing.

DAVINCI↗

NASA NTRSDate not supplied

Modeling of Particle Transport and Impact in Transient, Multiphase Oxidizer-Rich Environments Using Computational Fluid Dynamics and Lagrangian Particle Tracking

Particle impacts from foreign object debris (FOD) in an oxidizer-rich environment have been shown to be a credible and significant risk for ignition and failure of components and vehicles. The risk of particle ignition is dependent on many factors, including particle impact velocity/energy and fluid composition (i.e. fluid phase, species presence, and state). Prediction of particle transport and particle impacts in relevant environments, including transient, multiphase flows, is important for assessing the risk and avoiding repeated expensive system level tests. The capability to model both the fluid dynamics and particle transport in complex three-dimensional geometries and multiphase environments has been developed at Marshall Space Flight Center (MSFC) in the propulsion fluid dynamic branch (ER42) by utilizing computational fluid dynamics (CFD) simulations and Lagrangian particle tracking. Using CFD tools, including density-based Loci/CHEM with a cavitation model and pressure-based Loci/STREAM with a volume of fluids model, MSFC/ER42 has provided particle impact predictions to multiple projects for oxidizer compatibility assessments. Simulations of transient, multiphase environments such as liquid slugs flowing through tubing and cavitating flow in valves have been completed alongside one-way coupled Lagrangian particle tracking to predict particle impacts.

M.V. Fischels↗

NASA NTRS2023

Sea Ice Drift Tracks From Autonomous Buoys in the MOSAiC Distributed Network

A network of autonomous, ice-tethered buoys was deployed around the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in late September 2019 for a year-long drift in the Arctic Transpolar Drift Stream. The buoys were deployed as part of the MOSAiC distributed network (DN) which included 12 multi-instrumented ice stations and an additional 116 GPS buoys distributed primarily within a 40 km radius of the MOSAiC Central Observatory. Buoy coverage within the DN was maintained with additional deployments throughout the year-long drift allowing for collection of data over a full sea ice growth and melt cycle. All GPS position data from buoys deployed within the DN have been assembled and processed into the collection of 216 quality-controlled buoy drift tracks presented in this dataset covering the period 26 September 2019 – 23 May 2021. The drift tracks in this collection are ideal for studies of dynamic sea ice motion around the MOSAiC experiment at cascading spatial scales ranging from 100s of meters to 100s of km.

Angela C. Bliss↗

NASA NTRSDate not supplied

Suited User Incident Tracking System

The Suited User Incident Tracking System (SUITS) tracks all suited exposures during terrestrial analog simulations and trainings with the objective of recording any related issues, pains, or discomforts that arise from the exposure. This information is vital for informing where, how, and why issues are occurring during suited extravehicular activity (EVA) training and operations. The outputs of SUITS will be the foundation for the newly formed Suited Anomaly Assessment Team (SAAT) which consists of a broad range of EVA stakeholders including suit engineers, biomechanists, ergonomists, flight surgeons, athletic trainers, and physiologists. This team has been formed to provide robust, wholistic solutions to suit anomalies and issues identified by SUITS. SUITS data collected from September 2017 to June 2022 was analyzed for issue frequency and severity for each body location and plotted to visualize where issues were occurring. Clustering techniques using a k-modes approach were also applied to the data set to generate profiles of populations that experienced issues in the suit and populations that did not. A key finding identified by the SUITs analysis was that suited issues translate from predominantly upper body areas in microgravity space suits and associated analog simulations to lower body areas in planetary space suits and analog simulations. In addition, specific injury frequency and severity metrics were identified that will help drive requirements for commercially provided space suits. The SAAT will continue to meet on a biannual basis to identify trends in issues and injuries from the SUITS database to evaluate and develop solution strategies where needed for the purposes of suit design, EVA operations optimization, injury characterization and mitigation, and personalized improvements for human-suit interactions.

K. Dolick↗

NASA NTRSDate not supplied

Can Tracked Great Frigatebirds (Fregata minor) be Used to Measure the Dynamics of the Planetary Boundary Layer Height?

Observing the dynamics of the planetary boundary layer (PBL) will require creative combinations of space-based and in-situ measurements. Animals fitted with biologgers have been used to gather data and parameterize physical models in various settings and may be a useful addition to the suite of space-based measurements that NASA is considering. For example, great frigatebirds (Fregata minor) generally fly below 700m but have been shown to routinely climb up to 2,000 meters during the day, occasionally reaching heights over 4,000 meters. This suggests that they may be tracking boundary layer height dynamics as they soar and glide on air currents with little energetic cost. We show here that the high-altitude climbing heights of great frigatebirds carrying GPS/accelerometer biologgers (e-obs GmbH Bird Solar 15g) at Palmrya Atoll, Pacific Ocean, are consistent with the long-term climatology (2006-2019) of the local planetary boundary layer height, and that these soaring heights can be reliably extracted from the tag data. Additional study is needed to determine how well movement data from tracked birds can constrain PBL height, but this work demonstrates the potential for animal-borne sensors to complement space-based measurements. Biologging data were contributed by the USGS and the Nature Conservancy's Palmyra Bluewater Research (PBR) study and analyzed as part of NASA’s Internet of Animals project.

Planetary Boundary Layer Height↗

NASA NTRSDate not supplied

Modeling of Cavity Residence Time via Modeled Lagrangian Particle Tracking

One of the critical components in a scramjet is the cavity flame holder. In evaluating the sizing of this component, the residence time of the fuel in the cavity is a common parameter used. However, to obtain the residence time via CFD is an expensive undertaking. One method is to perform an LES simulation of the cavity and use Lagrangian particle tracking to obtain both the mean and probability density function of the time that the particles remain in the cavity. While this method affords a significant amount of information, it is very costly in CPU run time. A simpler method involves performing a time accurate RANS simulation of the cavity, and when converged, overlay a traceable scalar in the cavity region, and then record the decay of this scalar’s flux at a downstream location. The time scale of the decay rate can then be estimated and a residence time inferred. This method is less computationally expensive than the LES approach, but still requires a time-accurate solution while only providing a mean cavity residence time evaluation. In this paper a method of determining the mean cavity residence time as well as the Probability Density Function (PDF) of the residence time is proposed and demonstrated. This method is based on Lagrangian particle tracking modeled by the Generalized Langevin Equation and is implemented as a post-processing step for a steady RANS solution. Computational cost is on the order of minutes and the results are in agreement with values obtained by the LES and scalar decay methods.

Langevin↗

NASA NTRS2023

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information with Lower-latency NASA Data

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated datasets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast (GEOS-CF), daily historical (1980-present) concentrations of speciated PM2.5 based on the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (1) describing temporal and spatial trends in disease and potential environmental exposures, (2) identifying populations most affected, (3) generating hypotheses about associations between health and environmental exposures, and (4) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

air quality↗

NASA NTRSDate not supplied

The Feasibility of Motion Tracking Camera System for Magnetic Suspension Wind Tunnel Tests

The Entry Systems Modeling (ESM) Program at NASA has actively participated in the re-development of the Magnetic Suspension Balance System (MSBS) at the six-inch subsonic wind tunnel at NASA Langley Research Center. This initiative aims to enhance the MSBS system's capabilities, enabling the testing of stingless entry vehicle models at supersonic speeds. To achieve this, control algorithms are required to ensure magnetic levitation control and stability for models during free-oscillation dynamic responses. Currently, the system relies on electromagnetic position sensors to provide real-time 3 degrees of freedom in a rigid body. While this approach has proven successful for subsonic speeds, expanding testing under higher pressure conditions may necessitate the incorporation of real-time roll and pitch measurements to quantify the dynamic stability characteristics of the models in free-oscillation. In collaboration with Old Dominion University, the team at NASA Langley Research Center proposes the implementation of a motion-tracking camera system. This system will provide real-time five degrees of freedom output, which will be utilized within a closed feedback control system and a two-step system identification model to isolate aerodynamic forces from their corresponding magnetic forces. The motion-tracking cameras will offer precise and accurate control over the levitation system, facilitating precise and repeatable experiments within the wind tunnel. The real-time feedback provided by the cameras enables prompt adjustments to ensure the maintenance of stable levitation throughout the testing process.

Entry Systems Modeling↗

NASA NTRSDate not supplied

The Feasibility of Motion Tracking Camera System for Magnetic Suspension Wind Tunnel Tests

Entry Systems Modeling↗

NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗

NASA NTRSDate not supplied

Tracking the Hunga Tonga-Hunga Ha’apai Eruption Stratospheric Aerosol and Trace Gas Plumes Using Machine Learning

On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.

David M. Giles↗

NASA NTRSDate not supplied

Power and Propulsion Element Steerable High Gain Antenna Lunar Transit Thermal Analysis Tracking Methodology

The Power and Propulsion Element (PPE) is an ion thruster propulsion spacecraft developed as an element of Space Reactor (SR-1) Freedom to provide propulsion, communications and power for the spacecraft. PPE was originally being developed for the use with the lunar orbiting space station Gateway as one of the first two planned elements. PPE was to be launched with the Habitation and Logistics Outpost (HALO) element in a configuration called the Co-Manifested Vehicle (CMV) that would arrive at a Near-Rectilinear Halo Orbit (NRHO) around the Moon via a lunar transit spiral trajectory phase. The PPE communication system is equipped with two Steerable High Gain Antennas (SHGA) each steered by a two-axis gimbal (TAG) mechanism. A thermal analysis was conducted during the near-Earth spiral phase of the mission using Thermal Desktop (TD). This analysis utilized multiple axis Earth tracking articulators in combination with SINDA system internal environmental heating symbols to produce accurate Earth ground station tracking communication system temperatures. This presentation provides an overview of the communication system thermal model and the analysis methodology.

Thermal Analysis↗

DOE OSTI2021

Real-Time Location System Asset Tracking Using Wireless Networks

This work presents a wireless networking–based (Wi-Fi) infrastructure, with accompanying tags, to provide asset tracking in an industrial automation/manufacturing setting. The general principles described in this paper are applicable for most wireless technology variants used for asset tracking.

42 ENGINEERING↗