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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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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Research and Development in Optical Communications

A report in the form of lecture slides summarizes the optical-communications program of NASA s Jet Propulsion Laboratory (JPL) and describes the JPL Optical Communications Telescope Laboratory (OCTL) and its role in the program. The purpose of the program is to develop equipment and techniques for laser communication between (1) ground stations and (2) spacecraft (both near Earth and in deep space) and aircraft. The OCTL is an astronomical- style telescope facility that includes a 1-m-diameter, 75.8-m-focal length telescope in an elevation/azimuth mount, plus optical and electronic subsystems for tracking spacecraft and aircraft, receiving laser signals from such moving targets, and transmitting high-power laser signals to such targets. Near-term research at the OCTL is expected to focus on mitigating the effects of atmospheric scintillation on uplinks and on beacon-assisted tracking of ground stations by stations in deep space. Near-term experiments are expected to be performed with retroreflector-equipped aircraft and Earth-orbiting spacecraft techniques to test mathematical models of propagation of laser beams, multiple-beam strategies to mitigate uplink scintillation, and pointing and tracking accuracy of the telescope.

Wilson, Keith↗
NASA NTRS1991

The Telecommunications and Data Acquisition Report

This quarterly reports on space communications, radio navigation, radio science, and ground based radio and radar astronomy in connection with the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and in operations. Also included is standards activity at JPL for space data and information systems and DSN work. Specific areas of research are: Tracking and ground based navigation; Spacecraft and ground communications; Station control and system technology; DSN Systems Implementation; and DSN Operations.

Posner, E. C.↗
NASA NTRS1990

Ionospheric refraction effects on orbit determination using the orbit determination error analysis system

The influence of ionospheric refraction on orbit determination was studied through the use of the Orbit Determination Error Analysis System (ODEAS). The results of a study of the orbital state estimate errors due to the ionospheric refraction corrections, particularly for measurements involving spacecraft-to-spacecraft tracking links, are presented. In current operational practice at the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), the ionospheric refraction effects on the tracking measurements are modeled in the Goddard Trajectory Determination System (GTDS) using the Bent ionospheric model. While GTDS has the capability of incorporating the ionospheric refraction effects for measurements involving ground-to-spacecraft tracking links, such as those generated by the Ground Spaceflight Tracking and Data Network (GSTDN), it does not have the capability to incorporate the refraction effects for spacecraft-to-spacecraft tracking links for measurements generated by the Tracking and Data Relay Satellite System (TDRSS). The lack of this particular capability in GTDS raised some concern about the achievable accuracy of the estimated orbit for certain classes of spacecraft missions that require high-precision orbits. Using an enhanced research version of GTDS, some efforts have already been made to assess the importance of the spacecraft-to-spacecraft ionospheric refraction corrections in an orbit determination process. While these studies were performed using simulated data or real tracking data in definitive orbit determination modes, the study results presented here were obtained by means of covariance analysis simulating the weighted least-squares method used in orbit determination.

Yee, C. P.↗
NASA NTRS2017

Orbit Determination of the Lunar Reconnaissance Orbiter: Status After Seven Years

The Lunar Reconnaissance Orbiter (LRO) has been orbiting the Moon since 2009, obtaining unique and foundational datasets important to understanding the evolution of the Moon and the Solar System. The high-resolution data acquired by LRO benefit from precise orbit determination (OD), limiting the need for geolocation and co-registration tasks. The initial position knowledge requirement (50 m) was met with radio tracking from ground stations, after combination with LOLA altimetric crossovers. LRO-specific gravity field solutions were determined and allowed radio-only OD to perform at the level of 20 m, although secular inclination changes required frequent updates. The high-accuracy gravity fields from GRAIL, with <10 km spatial resolution, further improved the radio-only orbit reconstruction quality (<10 m). However, orbit reconstruction is in part limited by the 0.3-0.5 mm/s measurement noise level in S-band tracking. One-way tracking through Laser Ranging can supplement the tracking available for OD with 28-Hz ranges with 20-cm single-shot precision, but is available only on the nearside (the lunar hemisphere facing the Earth due to tidal locking). Here, we report on the status of the OD effort since the beginning of the mission, a period spanning more than seven years. We describe modeling improvements and the use of new measurements. In particular, the LOLA altimetric data give accurate, uniform, and independent information about LRO's orbit, with a different sensitivity and geometry which includes coverage over the lunar farside and is not tied to ground-based assets. With SLDEM2015 (a combination of the LOLA topographic profiles and the Kaguya Terrain Camera stereo images), another use of altimetry is possible for OD. We extend the 'direct altimetry' technique developed for the ICESat mission to perform OD and adjust spacecraft position to minimize discrepancies between LOLA tracks and SLDEM2015. Comparisons with the radio-only orbits are used to evaluate this new tracking type, of interest for the OD of future lunar orbiters carrying a laser altimeter. LROC NAC images also provide independent accuracy estimation, through the repeated views taken of anthropogenic features for instance.

Erwan Mazarico↗
NASA NTRS1991

SPECS: Orbital debris removal

The debris problem has reached a stage at which the risk to satellites and spacecraft has become substantial in low Earth orbit (LEO). This research discovered that small particles posed little threat to spacecraft because shielding can effectively prevent these particles from damaging the spacecraft. The research also showed that, even though collision with a large piece of debris could destroy the spacecraft, the large pieces of debris pose little danger because they can be tracked and the spacecraft can be maneuvered away from these pieces. Additionally, there are many current designs to capture and remove large debris particles from the space environment. From this analysis, it was decided to concentrate on the removal of medium-sized orbital debris, that is, those pieces ranging from 1 cm to 50 cm in size. The current design incorporates a transfer vehicle and a netting vehicle to capture the medium-sized debris. The system is based near an operational space station located at 28.5 deg inclination and 400 km altitude. The system uses ground-based tracking to determine the location of a satellite breakup or debris cloud. These data are uploaded to the transfer vehicle, which proceeds to rendezvous with the debris at a lower altitude parking orbit. Next, the netting vehicle is deployed, tracks the targeted debris, and captures it. After expending the available nets, the netting vehicle returns to the transfer vehicle for a new netting module and continues to capture more debris in the target area. Once all the netting modules are expended, the transfer vehicle returns to the space station's orbit where it is resupplied with new netting modules from a space shuttle load. The new modules are launched by the shuttle from the ground and the expended modules are taken back to Earth for removal of the captured debris, refueling, and repacking of the nets. Once the netting modules are refurbished, they are taken back into orbit for reuse. In a typical mission, the system has the ability to capture 50 pieces of orbital debris. One mission will take approximately six months and the system is designed to allow for a 30 deg inclination change on the outgoing and incoming trips of the transfer vehicle.

Source record↗
NASA NTRS1990

Final design of a space debris removal system

The objective is the removal of medium sized orbital debris in low Earth orbits. The design incorporates a transfer vehicle and a netting vehicle to capture the medium size debris. The system is based near an operational space station located at 28.5 degrees inclination and 400 km altitude. The system uses ground based tracking to determine the location of a satellite breakup or debris cloud. This data is unloaded to the transfer vehicle, and the transfer vehicle proceeds to rendezvous with the debris at a lower altitude parking orbit. Next, the netting vehicle is deployed, tracks the targeted debris, and captures it. After expending the available nets, the netting vehicle returns to the transfer vehicle for a new netting module and continues to capture more debris in the target area. Once all the netting modules are expended, the transfer vehicle returns to the space station's orbit, where it is resupplied with new netting modules from a space shuttle load. The new modules are launched by the shuttle from the ground, and the expended modules are taken back to Earth for removal of the captured debris, refueling, and repacking of the nets. Once the netting modules are refurbished, they are taken back into orbit for reuse. In a typical mission, the system has the ability to capture 50 pieces of orbital debris. One mission will take about six months. The system is designed to allow for a 30 degree inclination change on the outgoing and incoming trips of the transfer vehicle.

Carlson, Erika↗
NASA NTRS1985

Environment definition, small particles, diameter less than or equal to 1 MM

The collection of particles of diameters one millimeter and less far outnumbers the larger particle distribution in orbit. These small particles cannot be tracked from ground based radar as can the larger debris, therefore, there is greater uncertainty in their properties. The population is growing from contributions due to collisions of larger debris, explosions, and aluminum oxide particles from solid rocket motors. The solid rocket motor contribution is the prominent growth parameter, and the input from Space Shuttle deployed upper stages will range between 50,000 and 100,000 pounds per year. The environment is important because of the different design problems that will be posed to the engineer and scientist. The emphasis shifts from catastrophe deign, probability versus exposure time, and tracking-avoidance, to a continuous degradation problem.

Source record↗
NASA NTRS2019

Assessment of TLE-Based Orbit Determination and Prediction for Cubesats

The IceCube satellite is a 3U cubesat which was deployed from the International Space Station Nanoracks in May 2017. IceCube uses onboard Global Positioning System (GPS) measurements for both science data processing and orbit determination; additionally, IceCube uses Two Line Element (TLE) sets provided by USSTRATCOM through Space Track for ground station acquisition. Once acquired, GPS measurements are downlinked and can be verified against nearby TLE states.TLE sets are typically used for cubesat acquisition data, however the accuracy of their propagation has a limited lifespan which can cause issues when using an older TLE to attempt spacecraft acquisition. This presentation details the merits of TLE-based orbit determination and prediction and discusses techniques for improving both. These refinements allow for improved cubesat acquisition as well as calibration and on-orbit checkout of the GPS. Using IceCube data as representative of a typical cubesat, TLE states are simulated as tracking data and processed through an Extended Kalman Filter. This filtered solution provides not only an ongoing estimate of spacecraft drag state parameters, but also improves the definitive orbit determination estimation as well as the propagation accuracy and therefore spacecraft acquisition. Next, using the definitive TLE-based solution, raw GPS measurements are introduced into the filter where the combined measurement types allow the GPS measurements to be subsequently calibrated with respect to an unknown timing bias. These analyses provide a more accurate state estimation and prediction of cubesats during early orbit operations. Additionally, these techniques showcase methods for TLE-based state estimation and GPS calibration when other methods of tracking are unavailable.

Smith, Alexander↗
NASA NTRS2009

Lunar Navigation Architecture Design Considerations

The NASA Constellation Program is aiming to establish a long-term presence on the lunar surface. The Constellation elements (Orion, Altair, Earth Departure Stage, and Ares launch vehicles) will require a lunar navigation architecture for navigation state updates during lunar-class missions. Orion in particular has baselined earth-based ground direct tracking as the primary source for much of its absolute navigation needs. However, due to the uncertainty in the lunar navigation architecture, the Orion program has had to make certain assumptions on the capabilities of such architectures in order to adequately scale the vehicle design trade space. The following paper outlines lunar navigation requirements, the Orion program assumptions, and the impacts of these assumptions to the lunar navigation architecture design. The selection of potential sites was based upon geometric baselines, logistical feasibility, redundancy, and abort support capability. Simulated navigation covariances mapped to entry interface flightpath- angle uncertainties were used to evaluate knowledge errors. A minimum ground station architecture was identified consisting of Goldstone, Madrid, Canberra, Santiago, Hartebeeshoek, Dongora, Hawaii, Guam, and Ascension Island (or the geometric equivalent).

D'Souza, Christopher↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2024

Constraints on fifth forces and ultralight dark matter from OSIRIS-REx target asteroid Bennu

It is important to test the possible existence of fifth forces, as ultralight bosons that would mediate these are predicted to exist in several well-motivated extensions of the Standard Model. Recent work indicated asteroids as promising probes, but applications to real data are lacking so far. Here we use the OSIRIS-REx mission and ground-based tracking data for the asteroid Bennu to derive constraints on fifth forces. Our limits are strongest for mediator masses m ~ (10 -18 -10 -17 ) eV, where we currently achieve the tightest bounds. These can be translated to a wide class of models leading to Yukawa-type fifth forces, and we demonstrate how they apply to U(1) B dark photons and baryon-coupled scalars. Our results demonstrate the potential of asteroid tracking in probing well-motivated extensions of the Standard Model and ultralight bosons near the fuzzy dark matter range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1971

Navigation analysis for Viking 1979, option B

A parametric study performed for 48 trans-Mars reference missions in support of the Viking program is reported. The launch dates cover several months in the year 1979, and each launch date has multiple arrival dates in 1980. A plot of launch versus arrival dates with case numbers designated for reference purposes is included. The analysis consists of the computation of statistical covariance matrices based on certain assumptions about the ground-based tracking systems. The error model statistics are listed in tables. Tracking systems were assumed at three sites: Goldstone, California; Canberra, Australia; and Madrid, Spain. The tracking data consisted of range and Doppler measurements taken during the tracking intervals starting at E-30(d) and ending at E-10(d) for the control data and ending at E-18(h) for the knowledge data. The control and knowledge covariance matrices were delivered to the Planetary Mission Analysis Branch for inputs into a delta V dispersion analysis.

Mitchell, P. H.↗
NASA NTRS1974

Post-flight differential correction analysis using Vinti's spheroidal method for the small astronomy satellite orbit

The results of an intensive analysis of a differential orbit improvement method utilizing observational data for a 550-kilometer altitude, near-circular, near-equatorial satellite orbit are presented. Observations of the Small Astronomy Satellite (SAS-1) are in the form of direction cosines as measured at two ground interferometer tracking stations near the Equator during the first 22 orbital revolutions (approximately 37 hours) after launch of the spacecraft. Numerical results, in both tabular and graphical form, are displayed for numerous iterated fittings of various observational arcs by differential correction of the orbital elements. Parameters varied in these comparative cases include the time duration of the observational data block, the number of pairs of direction cosine data and the number of tracking station passes included in the solution, the distribution of such passes between the two available tracking stations, and the acceptance criterion for the observational residuals in the least squares fitting procedure. It was found that three observational pairs of direction cosine data, the minimum number possible for a uniquely determined solution in theory, are sufficient to promote covergence to an accurate solution, if properly selected.

Walden, H.↗