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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2023

Space Situational Awareness for Python

SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed and accuracy in mind and offers the following capabilities: - A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc. - Customizable force propagation models, including a variety of Earth gravity models, lunar gravity, radiation pressure, etc. - Multiple-hypothesis tracking (MHT) UCT linker - Vectorized computations - Short arc probabilistic orbit determination - Conjunction probability estimation - Uncertainty quantification - Monte Carlo data fusion - Support for multiple coordinate frames (with coordinate frame conversions)

Schlafly, Edward↗

NASA NTRS1971

Performance of the NASA laser ranging system in satellite tracking

NASA pulsed laser ranging systems for scientific satellite tracking, determining accuracy by trajectory and long arc orbital comparison

Johnson, T. S.↗

NASA NTRS1979

Base line estimation using single passes of laser data

The laser data of the GEOS 3 satellite passes observed by four stations at Greenbelt (Maryland), Bermuda, Grand Turk Island (Bahamas) and Patrick Air Force Base (Florida), were employed to determine precise interstation base lines and relative heights in short orbital arcs of no more than 12-min duration. No more than five arcs of data are required to define the interstation base lines to 30-cm precision. Base lines running parallel to the orbital motion can be defined to submeter precision from a single short arc of data. Combining arcs of different orbital geometry in a common adjustment of two or more stations relative to the base station helps to compensate for weak base line definition in any single arc. This technique can be used for tracking such spacecraft as Lageos, a high-altitude retroreflector-carrying satellite designed for precise laser ranging studies.

Dunn, P. J.↗

NASA NTRS2015

Precision Closed-Loop Orbital Maneuvering System Design and Performance for the Magnetospheric Multiscale Formation

NASAs Magnetospheric Multiscale (MMS) mission successfully launched on March 13,2015 (UTC) consists of four identically instrumented spin-stabilized observatories that function as a constellation to study magnetic reconnection in space. The need to maintain sufficiently accurate spatial and temporal formation resolution of the observatories must be balanced against the logistical constraints of executing overly-frequent maneuvers on a small fleet of spacecraft. These two considerations make for an extremely challenging maneuver design problem. This paper focuses on the design elements of a 6-DOF spacecraft attitude control and maneuvering system capable of delivering the high-precision adjustments required by the constellation designers specifically, the design, implementation, and on-orbit performance of the closed-loop formation-class maneuvers that include initialization, maintenance, and re-sizing. The maneuvering control system flown on MMS utilizes a micro-gravity resolution accelerometer sampled at a high rate in order to achieve closed-loop velocity tracking of an inertial target with arc-minute directional and millimeter-per second magnitude accuracy. This paper summarizes the techniques used for correcting bias drift, sensor-head offsets, and centripetal aliasing in the acceleration measurements. It also discusses the on-board pre-maneuver calibration and compensation algorithms as well as the implementation of the post-maneuver attitude adjustments.

Maneuver and Attitude Dynamics↗

NASA NTRS2015

Precision Closed-Loop Orbital Maneuvering System Design and Performance for the Magnetospheric Multi-Scale Mission (MMS) Formation

NASA's Magnetospheric Multi-Scale (MMS) mission successfully launched on March 13, 2015 (UTC) consists of four identically instrumented spin-stabilized observatories that function as a constellation to study magnetic reconnection in space. The need to maintain sufficiently accurate spatial and temporal formation resolution of the observatories must be balanced against the logistical constraints of executing overly-frequent maneuvers on a small fleet of spacecraft. These two considerations make for an extremely challenging maneuver design problem. This paper focuses on the design elements of a 6-DOF spacecraft attitude control and maneuvering system capable of delivering the high-precision adjustments required by the constellation designers---specifically, the design, implementation, and on-orbit performance of the closed-loop formation-class maneuvers that include initialization, maintenance, and re-sizing. The maneuvering control system flown on MMS utilizes a micro-gravity resolution accelerometer sampled at a high rate in order to achieve closed-loop velocity tracking of an inertial target with arc-minute directional and millimeter-per-second magnitude accuracy. This paper summarizes the techniques used for correcting bias drift, sensor-head offsets, and centripetal aliasing in the acceleration measurements. It also discusses the on-board pre-maneuver calibration and compensation algorithms as well as the implementation of the post-maneuver attitude adjustments.

Determination and Control↗

NASA NTRSDate not supplied

Airborne Remote Sensing Measurements of Particles in Different Parts of the World

Around the globe, atmospheric aerosols pose a significant yet uncertain impact on the Earth's climate, environmental air quality and human health. Suborbital sunphotometer measurements of Aerosol Optical Depth (AOD) (i.e., the amount of direct-beam solar light attenuated by aerosols within the atmospheric column) are used to validate satellite aerosol retrievals and are valuable when studying aerosol-solar radiation and/ or aerosol-cloud interactions. Since 1985, NASA Ames Research Center (ARC) has been using airborne sun-tracking sunphotometers to measure atmospheric constituents such as aerosols, clouds, and gases. The NASA Ames Airborne Tracking Sunphotometer (AATS-6) and then (AATS-14) operate by tracking the sun and measuring the transmission of solar radiation in 6 to 14 discrete spectral channels (Russell et al., 1986). The AATS systems were followed by the more advanced hyperspectral 4STAR instrument (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research; Dunagan et al., 2013), which combines the airborne sun-tracking capability of the AATS-14 with a sky scanning feature similar to the ground-based Aerosol Robotic Network Sun/sky photometers (AERONET). We present a comprehensive analysis of ~30 airborne campaigns undertaken by NASA and DoE based on a new database of airborne sunphotometer measurements. Using this database, we present a clear picture of airborne AODs over the range of historical campaigns and the aerosol sizes per region, especially over the ocean where AERONET data is limited. With this database, we can investigate systematic differences in AOD such as those observed over different land and ocean surfaces in specific geographical regions. Finally, we will briefly show comparisons with satellite aerosol retrievals from MODIS and/or VIIRS. Russell, P. B., T. Matsumoto, V. J. Banta, J. M. Livingston, C. Mina, D. S. Colburn, and R. F. Pueschel (1986), Measurements with an airborne, autotracking, external-head sunphotometer, Preprint Volume, Sixth Conference on Atmospheric Radiation, May 13–16, 1986, Amer. Meteor.Soc., Boston, MA, 55–58. Dunagan, Stephen E., et al. "Spectrometer for sky-scanning sun-tracking atmospheric research (4STAR): Instrument technology." Remote Sensing 5.8 (2013): 3872-3895

Brendan Stover Cornelison↗

NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

NASA NTRSDate not supplied

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

machine learning↗

NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗

NASA NTRSDate not supplied

arcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

machine learning↗

NASA NTRS1979

GEOS 3 STDN S band Doppler tracking investigation

GEOS 3S Doppler band and laser ranging data, acquired from August 1975 to March 1976 in the spacecraft altimeter calibration area, are examined. An evaluation of two-way and three-way Doppler data, for the positioning of Spaceflight Tracking and Data Network S band stations is presented, as well as the Goddard Space Flight Center laser system that is used to reference the exact position of the Doppler stations. The two-way and three-way Doppler tracking devices, situated at Rosman and Bermuda, have yielded data for the recovery of GEOS 3 arc height with an uncertainty of only 1 m. Attention is given to the effects of beacon signal frequency instability, controlled by a temperature sensitive auxiliary crystal oscillator on board the spacecraft, and to the one-way range rate tracking noise that was found to be within a range of 2 to 10 cm/s. 1- and 2-way passes and their different arc meters are graphed, showing the Doppler tracking interval. It was concluded that other accurate computations and recovery of station coordinates could be performed employing tracking data from S band stations.

Rosenbaum, B.↗

NASA NTRS1992

Contribution of Doppler and interferometric tracking during the Magellan approach to Venus

On May 4, 1989, the Magellan spacecraft began its 463 day and 1.3 billion km earth to Venus interplanetary cruise. Magellan's Venus approach trajectory required prediction accuracy of 6.1 seconds in arrival time and 126 km in the position of closest approach to achieve a desired Venus orbit. Data collection from Magellan's SAR required an elliptical orbit with an inclination between 84 deg and 86 deg to the Venus equator, a period between 3.1 and 3.3 hours, a periapsis altitude within 275 km and 325 km and a latitude of periapsis between 0 deg and 10 deg North. Predictions of Magellan's arrival time and closest approach to Venus were derived from cruise trajectories determined exclusively from coherent two-way Doppler using both S-band (2.3 GHz) uplink/downlink and X-band (8.4 GHz) uplink/downlink and X-band spacecraft-quasar interferometric delay data. Analysis of data reduction strategies employing various data arc lengths and data combinations shows that interferometric tracking data, used in conjunction with Doppler, improved trajectory solution accuracy and robustness.

Graat, E. J.↗

NASA NTRS1994

A geopotential model from satellite tracking, altimeter, and surface gravity data: GEM-T3

An improved model of Earth's gravitational field, Goddard Earth Model T-3 (GEM-T3), has been developed from a combination of satellite tracking, satellite altimeter, and surface gravimetric data. GEM-T3 provides a significant improvement in the modeling of the gravity field at half wavelengths of 400 km and longer. This model, complete to degree and order 50, yields more accurate satellite orbits and an improved geoid representation than previous Goddard Earth Models. GEM-T3 uses altimeter data from GEOS 3 (1975-1976), Seasat (1978) and Geosat (1986-1987). Tracking information used in the solution includes more than 1300 arcs of data encompassing 31 different satellites. The recovery of the long-wavelength components of the solution relies mostly on highly precise satellite laser ranging (SLR) data, but also includes Tracking Network (TRANET) Doppler, optical, and satellite-to-satellite tracking acquired between the ATS 6 and GEOS 3 satellites. The main advances over GEM-T2 (beyond the inclusion of altimeter and surface gravity information which is essential for the resolution of the shorter wavelength geoid) are some improved tracking data analysis approaches and additional SLR data. Although the use of altimeter data has greatly enhanced the modeling of the ocean geoid between 65 deg N and 60 deg S latitudes in GEM-T3, the lack of accurate detailed surface gravimetry leaves poor geoid resolution over many continental regions of great tectonic interest (e.g., Himalayas, Andes). Estimates of polar motion, tracking station coordinates, and long-wavelength ocean tidal terms were also made (accounting for 6330 parameters). GEM-T3 has undergone error calibration using a technique based on subset solutions to produce reliable error estimates. The calibration is based on the condition that the expected mean square deviation of a subset gravity solution from the full set values is predicted by the solutions' error covariances. Data weights are iteratively adjusted until this condition for the error calibration is satisfied. In addition, gravity field tests were performed on strong satellite data sets withheld from the solution (thereby ensuring their independence). In these tests, the performance of the subset models on the withheld observations is compared to error projections based on their calibrated error covariances. These results demonstrate that orbit accuracy projections are reliable for new satellites which were not included in GEM-T3.

Lerch, F. J.↗

NASA NTRS1997

Few arc-minute and keV resolutions with the TIGRE Compton telescope

The tracking and imaging gamma ray experiment (TIGRE) Compton telescope concept can provide an angular resolution of a few arcmin, an energy resolution of a few keV and high sensitivity, while providing the wide field of view necessary for surveying and monitoring observations. Silicon and CdZnTe strip detectors are used to detect Compton pair events and determine their incident directions and energies. Above 400 keV, Compton recoil electrons are tracked through successive layers of thin silicon strip detectors. Compton scattered photons are detected with CdZnTe strip detectors. Pair electrons and positrons are tracked to provide high sensitivity observations in the 10 to 100 MeV range. Polarization studies are performed with large angle Compton scatter events. The TIGRE concept and development status are described.

Zych, A.↗

NASA NTRS1992

An improved model of the Earth's gravity field - GEM-T3

An improved model of the Earth's gravitational field is developed from a combination of conventional satellite tracking, satellite altimeter measurements, and surface gravimetric data (GEM-T3). This model gives improved performance for the computation of satellite orbital effects as well as a superior representation of the geoid from that achieved in any previous Goddard Earth Model. The GEM-T3 model uses altimeter data directly to define the orbits, geoid, and dynamic height fields. Altimeter data acquired during the GEOS-3 (1975-1976), SEASAT (1978), and GEOSAT (1986-1987) missions were used to compute GEM-T3. In order to accommodate the non-gravitational signal mapped by these altimeters, spherical harmonic models of the dynamic height of the ocean surface were recovered for each mission simultaneously with the gravitational field. The tracking data utilized in the solution includes more than 1300 arcs of data encompassing 31 different satellites. The observational data base is highly dependent on SLR, but also includes TRANET Doppler, optical, S-Band average range-rate and satellite-to-satellite tracking acquired between ATS-6 and GEOS-3. The GEM-T3 model has undergone extensive error calibration.

Nerem, R. S.↗

NASA NTRS1981

Cometary ephemerides - needs and concerns

With the use of narrow field-of-view instrumentation on faint comets, the accuracy requirements upon computed ephemerides are increasing. It is not uncommon for instruments with a one arc minute field-of-view to be tracking a faint comet that is not visible without a substantial integration time. As with all ephemerides of solar syste objects, the computed motion and reduction of these observations, the computed motion of a comet is further depenent upon effects related to the comet's activity. Thus, the ephemeris of an active comet is corrupted by both observational errors and errors due to the comet's activity.

Yeomans, D. K.↗

NASA NTRS1983

Radio metric orbit determination for the Giotto mission to Comet Halley

An international fleet of five spacecraft will fly past Comet Halley as it travels through the inner solar system in early 1986. This paper discusses orbit determination problems associated with the Giotto spacecraft, sponsored by the European Space Agency. The large number of spin axis precession maneuvers required to maintain the desired spacecraft attitude creates a new kind of radio metric orbit determination problem for this mission. This paper investigates the accuracy with which the Giotto spacecraft orbit can be determined relative to the earth or the sun, and establishes the sensitivity of this accuracy to the selection of the parameters to be estimated, the form of estimator used, the number of tracking stations employed, the length of the data arc, the selection of data types processed, and the levels of various error sources.

Wood, L. J.↗

NASA NTRSDate not supplied

ArcjetCV: Automating Arc Jet Analysis

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗