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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Small Orbital Stereo Tracking Camera Technology Development

On-Orbit Small Debris Tracking and Characterization is a technical gap in the current National Space Situational Awareness necessary to safeguard orbital assets and crew. This poses a major risk of MOD damage to ISS and Exploration vehicles. In 2015 this technology was added to NASA's Office of Chief Technologist roadmap. For missions flying in or assembled in or staging from LEO, the physical threat to vehicle and crew is needed in order to properly design the proper level of MOD impact shielding and proper mission design restrictions. Need to verify debris flux and size population versus ground RADAR tracking. Use of ISS for In-Situ Orbital Debris Tracking development provides attitude, power, data and orbital access without a dedicated spacecraft or restricted operations on-board a host vehicle as a secondary payload. Sensor Applicable to in-situ measuring orbital debris in flux and population in other orbits or on other vehicles. Could enhance safety on and around ISS. Some technologies extensible to monitoring of extraterrestrial debris as well To help accomplish this, new technologies must be developed quickly. The Small Orbital Stereo Tracking Camera is one such up and coming technology. It consists of flying a pair of intensified megapixel telephoto cameras to evaluate Orbital Debris (OD) monitoring in proximity of International Space Station. It will demonstrate on-orbit optical tracking (in situ) of various sized objects versus ground RADAR tracking and small OD models. The cameras are based on Flight Proven Advanced Video Guidance Sensor pixel to spot algorithms (Orbital Express) and military targeting cameras. And by using twin cameras we can provide Stereo images for ranging & mission redundancy. When pointed into the orbital velocity vector (RAM), objects approaching or near the stereo camera set can be differentiated from the stars moving upward in background.

Bryan, Tom↗
NASA NTRS1978

System and method for tracking a signal source

A system for tracking moving signal sources is disclosed which is particularly adaptable for use in tracking stage performers. A miniature transmitter is attached to the person or object to be tracked and emits a detectable signal of a predetermined frequency. A plurality of detectors positioned in a preset pattern sense the signal and supply output information to a phase detector which applies signals representing the angular orientation of the transmitter to a computer. The computer provides command signals to a servo network which drives a device such as a motor driven mirror reflecting the beam of a spotlight, to track the moving transmitter.

Mogavero, L. N.↗
NASA NTRS2010

Optical Photometric Observations of GEO Debris

We report on a continuing program of optical photometric measurements of faint orbital debris at geosynchronous Earth orbit (GEO). These observations can be compared with laboratory studies of actual spacecraft materials in an effort to determine what the faint debris at GEO may be. We have optical observations from Cerro Tololo Inter-American Observatory (CTIO) in Chile of two samples of debris: 1. GEO objects discovered in a survey with the University of Michigan's 0.6-m aperture Curtis-Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope), and then followed up in real-time with the CTIO/SMARTS 0.9-m for orbits and photometry. Our goal is to determine 6 parameter orbits and measure colors for all objects fainter than R = 15 t11 magnitude that are discovered in the MODEST survey. 2. A smaller sample of high area to mass ratio (AMR) objects discovered independently, and acquired using predictions from orbits derived from independent tracking data collected days prior to the observations. Our optical observations in standard astronomical BVRI filters are done with either telescope, and with the telescope tracking the debris object at the object's angular rate. Observations in different filters are obtained sequentially. We have obtained 71 calibrated sequences of R-B-V-I-R magnitudes. A total of 66 of these sequences have 3 or more good measurements in all filters (not contaminated by star streaks or in Earth's shadow). Most of these sequences show brightness variations, but a small subset has observed brightness variations consistent with that expected from observational errors alone. The majority of these stable objects are redder than a solar color in both B-R and R-I. There is no dependence on color with brightness. For a smaller sample of objects we have observed with synchronized CCD cameras on the two telescopes. The CTIO 0.9-m observes in B, and MODEST in R. The CCD cameras are electronically linked together so that the start time and duration of observations are the same to better than 50 milliseconds. Thus, the B-R color is a true measure of the surface of the debris piece facing the telescopes for that observation. Any change in color reflects a real change in the debris surface. We will compare our observations with models and laboratory measurements of selected surfaces.

Seitzer, Patrick↗
DOE OSTI2023

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

NORAD's PARCS small satellite tests (1976 and 1978)

NORAD sponsored small satellite tests in 1976 and 1978. The purpose of the tests was to use their more sensitive radar to determine the number of Earth orbiting objects which are not part of the official catalogue. Both tests used the PARCS radar. The characteristics of this radar are given. The detection capability of NORAD's operational system is estimated and compared to the PARC's radar sensitivity during these tests. The tests only slightly improved the detection capability, and the largest improvements were at the lowest and highest regions of its sensitivity range. The major conclusion of the test is that 17.7% of the objects detected were uncorrelated (i.e., not in the official catalogue). However, perhaps most significant is the altitutde and size distribution of detected objects are illustrated. The 1978 results are also summarized. This test concluded that at least 7% of the objects detected were not in the official catalogue. Another 6% of the detected objects were not tracked well enough to determine their status. Again, a large percentage of the detected objects at lower altitudes were not in the catalogue.

Kessler, D. J.↗
NASA NTRS1990

Robot tracking system improvements and visual calibration of orbiter position for radiator inspection

The following separate topics are addressed: (1) improving a robotic tracking system; and (2) providing insights into orbiter position calibration for radiator inspection. The objective of the tracking system project was to provide the capability to track moving targets more accurately by adjusting parameters in the control system and implementing a predictive algorithm. A computer model was developed to emulate the tracking system. Using this model as a test bed, a self-tuning algorithm was developed to tune the system gains. The model yielded important findings concerning factors that affect the gains. The self-tuning algorithms will provide the concepts to write a program to automatically tune the gains in the real system. The section concerning orbiter position calibration provides a comparison to previous work that had been performed for plant growth. It provided the conceptualized routines required to visually determine the orbiter position and orientation. Furthermore, it identified the types of information which are required to flow between the robot controller and the vision system.

Tonkay, Gregory↗
NASA NTRS1994

Mark Tracking: Position/orientation measurements using 4-circle mark and its tracking experiments

Future space robots require position and orientation tracking with visual feedback control to track and capture floating objects and satellites. We developed a four-circle mark that is useful for this purpose. With this mark, four geometric center positions as feature points can be extracted from the mark by simple image processing. We also developed a position and orientation measurement method that uses the four feature points in our mark. The mark gave good enough image measurement accuracy to let space robots approach and contact objects. A visual feedback control system using this mark enabled a robot arm to track a target object accurately. The control system was able to tolerate a time delay of 2 seconds.

Kanda, Shinji↗
NASA NTRS2011

Bit of History and Some Lessons Learned in Using NASA Remote Sensing Data in Public Health Applications

The NASA Applied Sciences Program's public health initiative began in 2004 to illustratethe potential benefits for using remote sensing in public health applications. Objectives/Purpose: The CDC initiated a st udy with NASA through the National Center for Environmental Health (NCEH) to establish a pilot effort to use remote sensing data as part of its Environmental Public Health Tracking Network (EPHTN). As a consequence, the NCEH and NASA developed a project called HELIX-Atlanta (Health and Environment Linkage for Information Exchange) to demonstrate a process for developing a local environmental public health tracking and surveillance network that integrates non-infectious health and environment systems for the Atlanta metropolitan area. Methods: As an ongo ing, systematic integration, analysis and interpretation of data, an EPHTN focuses on: 1 -- environmental hazards; 2 -- human exposure to environmental hazards; and 3 -- health effects potentially related to exposure to environmental hazards. To satisfy the definition of a surveillance system the data must be disseminated to plan, implement, and evaluate environmental public health action. Results: A close working r elationship developed with NCEH where information was exchanged to assist in the development of an EPHTN that incorporated NASA remote sensing data into a surveillance network for disseminating public health tracking information to users. This project?s success provided NASA with the opportunity to work with other public health entities such as the University of Mississippi Medical Center, the University of New Mexico and the University of Arizona. Conclusions: HELIX-Atlanta became a functioning part of the national EPHTN for tracking environmental hazards and exposure, particularly as related to air quality over Atlanta. Learning Objectives: 1 -- remote sensing data can be integral to an EPHTN; 2 -- public tracking objectives can be enhanced through remote sensing data; 3 -- NASA's involvement in public health applications can have wider benefits in the future.

Quattrochi, Dale A.↗
NASA NTRS2009

Apollo Mission Techniques Lunar Orbit Activities - Part 1a

This slide presentation reviews the planned sequence of events and the rationale for all lunar missions, and the flight experiences and lessons learned for the lunar orbit activities from a trajectory perspective. Shown are trajectories which include the moon's position at the various stages in the complete trip from launch, to the return and reentry. Included in the presentation are objectives and the sequence of events,for the Apollo 8, and Apollo 10. This is followed by a discussion of Apollo 11, including: the primary mission objective, the sequence of events, and the flight experience. The next mission discussed was Apollo 12. It reviews the objectives, the ground tracking, procedure changes, and the sequence of events. The aborted Apollo 13 mission is reviewed, including the objectives, and the sequence of events. Brief summaries of the flight experiences for Apollo 14-16 are reviewed. The flight sequence of events of Apollo 17 are discussed. In summary each mission consistently performing precision landings required that Apollo lunar orbit activities devote considerable attention to: (1) Improving fidelity of lunar gravity models, (2) Maximizing availability of ground tracking, (3) Minimizing perturbations on the trajectory, (4) Maximizing LM propellant reserves for hover time. Also the use of radial separation maneuvers (1) allows passive re-rendezvous after each rev, but ... (2) sensitive to small dispersions in initial sep direction

Interbartolo, Michael A.↗
DOE OSTI2023

Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection

As the operational time window of experimental rotating detonation engines (RDEs) is expanded and the technology matures toward integration within gas turbines, monitoring techniques must evolve to offer computationally efficient and highly time-resolved diagnostics. In this study, computer vision object detection methodology that seeks to reduce data processing time and calculate wave velocity within drastically reduced time intervals as compared to traditional high-frame-rate RDE images analysis techniques is proposed. The adapted you-only-look-once object detection network is trained to detect individual detonation waves within single down-axis RDE images. The wave location and rotational direction detected within a frame are tracked through a series of high-speed images to calculate the frame-to-frame wave velocity with the time-step resolution of $\mathrm{20 μs}$ across a series of frames. The analysis of the annotation box size and image linearization effects is presented, demonstrating the lowest frame-to-frame velocity total uncertainty of $\mathrm{±3.8\%}$ and the highest classification speed of 9.5 frames per second using linearized images. Linearized images “unwrap” the RDE annulus pixel region to a reduced image size. Here, this new method offers great reductions in data processing times and unsteady detonation behavior insight at intervals more comparable to the timescales of detonation wave interactions via the application of machine learning to experimental RDE data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Artificial Intelligence-Assisted Daytime Video Monitoring for Bird, Insect, and Other Wildlife Interactions with Photovoltaic Solar Energy Facilities

Studying bird, insect, and other wildlife interactions with photovoltaic (PV) solar energy facilities is difficult due to limited multi-season, multi-site data. Researchers can address such data gaps by combining passive monitoring and artificial intelligence (AI). As a part of the development of AI-enabled avian–solar monitoring software, we collected over 19,000 h of daytime videos at five PV sites across three U.S. regions between 2019 and 2024. We applied a moving object detection and tracking (MODT Version 1) AI model we developed earlier to 4373 h of the footage to extract moving objects in video frames, and human reviewers interpreted the model output and identified 68,646 bird, 25,968 insect, and 169 other wildlife instances to generate the training/validation dataset. We analyzed the data by site, region, and season, considering ground cover and landscapes. Songbirds were most common, with raptors as the next most frequent group. Most notably, no bird collisions were confirmed in our observations collected from the videos. Birds most often flew over or near panels, with the highest observations in the Midwest and Northeast (approximately 30 observations per hour on average) and fewer in the desert Southwest. Other behaviors included perching, foraging, and nesting. Bird abundance peaked during breeding and migration seasons. AI-assisted video monitoring proved effective for non-invasively studying flying wildlife at solar facilities to inform ecologically mindful energy development.

avian mortality↗
NASA NTRS2014

Bi-static Optical Observations of GEO Objects

A bi-static study of objects at Geosynchronous Earth Orbit (GEO) was conducted using two ground-based wide-field optical telescopes. The University of Michigan's 0.6-m MODEST (Michigan Orbital Debris Survey Telescope) located at the Cerro Tololo Inter- American Observatory in Chile was employed in a series of coordinated observations with the U.S. Naval Observatory's (USNO) 1.3-m telescope at the USNO Flagstaff Station near Flagstaff, Arizona, USA. The goals of this project are twofold: (1) Obtain optical distances to known and unknown objects at GEO from the difference in the observed topocentric position of objects measured with respect to a reference star frame. The distance can be derived directly from these measurements, and is independent of any orbital solution. The wide geographical separation of these two telescopes means that the parallax difference is larger than ten degrees, and (2) Compare optical photometry in similar filters of GEO objects taken during the same time period from the two sites. The object's illuminated surfaces presented different angles of reflected sunlight to the two telescopes.During a four hour period on the night.of 22 February 2014 (UT), coordinated observations were obtained for eight different GEO positions. Each coordinated observation sequence was started on the hour or half-hour, and was selected to ensure the same cataloged GEO object was available in the field of view of both telescopes during the thirty minute observing sequence. GEO objects were chosen to be both controlled and uncontrolled at a range of orbital inclinations, and the objects were not tracked. Instead both telescopes were operated with all drives off in GEO survey mode to discover un-cataloged objects at GEO. The initial results from this proof-of-concept observing run will be presented, with the intent of laying the foundation for future large-scale bi-static observing campaigns of the GEO regime.

Seitzer, Patrick↗
NASA NTRS1989

Multiple cooperating manipulators: The case of kinematically redundant arms

Existing work concerning two or more manipulators simultaneously grasping and transferring a common load is continued and extended. Specifically considered is the case of one or more arms being kinematically redundant. Some existing results in the modeling and control of single redundant arms and multiple manipulators are reviewed. The cooperating situation is modeled in terms of a set of coordinates representing object motion and internal object squeezing. Nominal trajectories in these coordinates are produced via actuator load distribution algorithms introduced previously. A controller is developed to track these desired object trajectories while making use of the kinematic redundancy to additionally aid the cooperation and coordination of the system. It is shown how the existence of kinematic redundancy within the system may be used to enhance the degree of cooperation achievable.

Walker, Ian D.↗
NASA NTRS1993

The Ultraviolet Plume Instrument (UVPI)

The Ultraviolet Plume Instrument (UVPI) was launched aboard the Low-power Atmospheric Compensation Experiment (LACE) satellite on 14 Feb. 1990. Both the spacecraft and the UVPI were sponsored by the Directed Energy Office of the Strategic Defense Initiative Organization. The mission of the UVPI was to obtain radiometrically calibrated images of rocket plumes at high altitude and background image data of the Earth, Earth's limb, and celestial objects in the near- and middle-UV wave bands. The UVPI was designed for nighttime observations, i.e., to acquire and track relatively bright objects against a dark background.

Horan, D. M.↗
NASA NTRS2011

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

Chien, Chiun-Hong↗